id sid tid token lemma pos cana-616 1 1 communications communication NOUN cana-616 1 2 on on ADP cana-616 1 3 applied apply VERB cana-616 1 4 nonlinear nonlinear ADJ cana-616 1 5 analysis analysis NOUN cana-616 1 6 issn issn NOUN cana-616 1 7 : : PUNCT cana-616 1 8 1074 1074 NUM cana-616 1 9 - - PUNCT cana-616 1 10 133x 133x NUM cana-616 1 11 vol vol NOUN cana-616 1 12 31 31 NUM cana-616 1 13 no no NOUN cana-616 1 14 . . PUNCT cana-616 2 1 2s 2s NUM cana-616 2 2 ( ( PUNCT cana-616 2 3 2024 2024 NUM cana-616 2 4 ) ) PUNCT cana-616 2 5 118 118 NUM cana-616 2 6 https://internationalpubls.com https://internationalpubls.com X cana-616 2 7 statistical statistical ADJ cana-616 2 8 assessment assessment NOUN cana-616 2 9 of of ADP cana-616 2 10 bayesian bayesian NOUN cana-616 2 11 optimization optimization NOUN cana-616 2 12 gradient gradient NOUN cana-616 2 13 and and CCONJ cana-616 2 14 hessian hessian ADJ cana-616 2 15 computation computation NOUN cana-616 2 16 based base VERB cana-616 2 17 improved improve VERB cana-616 2 18 random random ADJ cana-616 2 19 forest forest NOUN cana-616 2 20 classifier classifier NOUN cana-616 2 21 for for ADP cana-616 2 22 nonlinear nonlinear ADJ cana-616 2 23 classification classification NOUN cana-616 2 24 problems problem NOUN cana-616 2 25 dr dr PROPN cana-616 2 26 . . PROPN cana-616 2 27 sunil sunil PROPN cana-616 2 28 kumar kumar PROPN cana-616 2 29 gupta1 gupta1 PROPN cana-616 2 30 , , PUNCT cana-616 2 31 dr dr PROPN cana-616 2 32 . . PROPN cana-616 2 33 m m PROPN cana-616 2 34 venu venu PROPN cana-616 2 35 gopala gopala PROPN cana-616 2 36 rao2 rao2 PROPN cana-616 2 37 , , PUNCT cana-616 2 38 dr dr PROPN cana-616 2 39 . . PROPN cana-616 2 40 babita babita PROPN cana-616 2 41 jain3 jain3 PROPN cana-616 2 42 , , PUNCT cana-616 2 43 ashish ashish PROPN cana-616 2 44 raj4 raj4 PROPN cana-616 2 45 1professor 1professor NUM cana-616 2 46 , , PUNCT cana-616 2 47 department department NOUN cana-616 2 48 of of ADP cana-616 2 49 electrical electrical ADJ cana-616 2 50 and and CCONJ cana-616 2 51 electronics electronic NOUN cana-616 2 52 engineering engineering NOUN cana-616 2 53 , , PUNCT cana-616 2 54 poornima poornima PROPN cana-616 2 55 university university PROPN cana-616 2 56 , , PUNCT cana-616 2 57 jaipur jaipur PROPN cana-616 2 58 , , PUNCT cana-616 2 59 ( ( PUNCT cana-616 2 60 india india PROPN cana-616 2 61 ) ) PUNCT cana-616 2 62 2professor 2professor PROPN cana-616 2 63 & & CCONJ cana-616 2 64 principal principal NOUN cana-616 2 65 , , PUNCT cana-616 2 66 navkis navkis PROPN cana-616 2 67 college college PROPN cana-616 2 68 of of ADP cana-616 2 69 engineering engineering PROPN cana-616 2 70 , , PUNCT cana-616 2 71 hassan hassan PROPN cana-616 2 72 , , PUNCT cana-616 2 73 karnataka karnataka PROPN cana-616 2 74 ( ( PUNCT cana-616 2 75 india india PROPN cana-616 2 76 ) ) PUNCT cana-616 2 77 3professor 3professor NUM cana-616 2 78 , , PUNCT cana-616 2 79 navkis navkis PROPN cana-616 2 80 college college NOUN cana-616 2 81 of of ADP cana-616 2 82 engineering engineering PROPN cana-616 2 83 , , PUNCT cana-616 2 84 hassan hassan PROPN cana-616 2 85 , , PUNCT cana-616 2 86 karnataka karnataka PROPN cana-616 2 87 ( ( PUNCT cana-616 2 88 india india PROPN cana-616 2 89 ) ) PUNCT cana-616 2 90 4associate 4associate PROPN cana-616 2 91 professor professor NOUN cana-616 2 92 , , PUNCT cana-616 2 93 department department NOUN cana-616 2 94 of of ADP cana-616 2 95 electrical electrical ADJ cana-616 2 96 and and CCONJ cana-616 2 97 electronics electronic NOUN cana-616 2 98 engineering engineering NOUN cana-616 2 99 , , PUNCT cana-616 2 100 poornima poornima PROPN cana-616 2 101 university university PROPN cana-616 2 102 , , PUNCT cana-616 2 103 jaipur jaipur PROPN cana-616 2 104 , , PUNCT cana-616 2 105 ( ( PUNCT cana-616 2 106 india india PROPN cana-616 2 107 ) ) PUNCT cana-616 2 108 * * PUNCT cana-616 2 109 author author NOUN cana-616 2 110 for for ADP cana-616 2 111 correspondence correspondence NOUN cana-616 2 112 e e NOUN cana-616 2 113 - - NOUN cana-616 2 114 mail mail NOUN cana-616 2 115 : : PUNCT cana-616 2 116 sunil.gupta@poornima.edu.in sunil.gupta@poornima.edu.in ADJ cana-616 2 117 article article NOUN cana-616 2 118 history history NOUN cana-616 2 119 : : PUNCT cana-616 2 120 received receive VERB cana-616 2 121 : : PUNCT cana-616 2 122 08 08 NUM cana-616 2 123 - - SYM cana-616 2 124 03 03 NUM cana-616 2 125 - - PUNCT cana-616 2 126 2024 2024 NUM cana-616 2 127 revised revise VERB cana-616 2 128 : : PUNCT cana-616 2 129 26 26 NUM cana-616 2 130 - - PUNCT cana-616 2 131 04 04 NUM cana-616 2 132 - - PUNCT cana-616 2 133 2024 2024 NUM cana-616 2 134 accepted accept VERB cana-616 2 135 : : PUNCT cana-616 2 136 15 15 NUM cana-616 2 137 - - SYM cana-616 2 138 05 05 NUM cana-616 2 139 - - PUNCT cana-616 2 140 2024 2024 NUM cana-616 2 141 abstract abstract NOUN cana-616 2 142 : : PUNCT cana-616 2 143 this this DET cana-616 2 144 study study NOUN cana-616 2 145 introduces introduce VERB cana-616 2 146 an an DET cana-616 2 147 enhanced enhance VERB cana-616 2 148 random random ADJ cana-616 2 149 forest forest NOUN cana-616 2 150 classifier classifier NOUN cana-616 2 151 , , PUNCT cana-616 2 152 optimized optimize VERB cana-616 2 153 using use VERB cana-616 2 154 a a DET cana-616 2 155 novel novel ADJ cana-616 2 156 bayesian bayesian NOUN cana-616 2 157 optimization optimization NOUN cana-616 2 158 approach approach NOUN cana-616 2 159 that that PRON cana-616 2 160 incorporates incorporate VERB cana-616 2 161 gradient gradient ADJ cana-616 2 162 and and CCONJ cana-616 2 163 hessian hessian ADJ cana-616 2 164 computations computation NOUN cana-616 2 165 . . PUNCT cana-616 3 1 our our PRON cana-616 3 2 objective objective NOUN cana-616 3 3 was be AUX cana-616 3 4 to to PART cana-616 3 5 improve improve VERB cana-616 3 6 the the DET cana-616 3 7 model model NOUN cana-616 3 8 's 's PART cana-616 3 9 accuracy accuracy NOUN cana-616 3 10 and and CCONJ cana-616 3 11 computational computational ADJ cana-616 3 12 efficiency efficiency NOUN cana-616 3 13 when when SCONJ cana-616 3 14 applied apply VERB cana-616 3 15 to to ADP cana-616 3 16 this this DET cana-616 3 17 specific specific ADJ cana-616 3 18 type type NOUN cana-616 3 19 of of ADP cana-616 3 20 image image NOUN cana-616 3 21 data datum NOUN cana-616 3 22 . . PUNCT cana-616 4 1 we we PRON cana-616 4 2 conducted conduct VERB cana-616 4 3 a a DET cana-616 4 4 series series NOUN cana-616 4 5 of of ADP cana-616 4 6 experiments experiment NOUN cana-616 4 7 to to PART cana-616 4 8 statistically statistically ADV cana-616 4 9 assess assess VERB cana-616 4 10 the the DET cana-616 4 11 performance performance NOUN cana-616 4 12 of of ADP cana-616 4 13 our our PRON cana-616 4 14 proposed propose VERB cana-616 4 15 classifier classifier NOUN cana-616 4 16 against against ADP cana-616 4 17 conventional conventional ADJ cana-616 4 18 models model NOUN cana-616 4 19 . . PUNCT cana-616 5 1 using use VERB cana-616 5 2 a a DET cana-616 5 3 robust robust ADJ cana-616 5 4 dataset dataset NOUN cana-616 5 5 of of ADP cana-616 5 6 annotated annotate VERB cana-616 5 7 images image NOUN cana-616 5 8 depicting depict VERB cana-616 5 9 various various ADJ cana-616 5 10 stages stage NOUN cana-616 5 11 of of ADP cana-616 5 12 lumpy lumpy ADJ cana-616 5 13 skin skin NOUN cana-616 5 14 disease disease NOUN cana-616 5 15 , , PUNCT cana-616 5 16 our our PRON cana-616 5 17 model model NOUN cana-616 5 18 demonstrated demonstrate VERB cana-616 5 19 superior superior ADJ cana-616 5 20 performance performance NOUN cana-616 5 21 in in ADP cana-616 5 22 terms term NOUN cana-616 5 23 of of ADP cana-616 5 24 accuracy accuracy NOUN cana-616 5 25 , , PUNCT cana-616 5 26 sensitivity sensitivity NOUN cana-616 5 27 , , PUNCT cana-616 5 28 and and CCONJ cana-616 5 29 specificity specificity NOUN cana-616 5 30 . . PUNCT cana-616 6 1 bayesian bayesian NOUN cana-616 6 2 optimization optimization NOUN cana-616 6 3 effectively effectively ADV cana-616 6 4 tuned tune VERB cana-616 6 5 the the DET cana-616 6 6 hyperparameters hyperparameter NOUN cana-616 6 7 of of ADP cana-616 6 8 the the DET cana-616 6 9 classifier classifier NOUN cana-616 6 10 , , PUNCT cana-616 6 11 leading lead VERB cana-616 6 12 to to ADP cana-616 6 13 significant significant ADJ cana-616 6 14 improvements improvement NOUN cana-616 6 15 in in ADP cana-616 6 16 learning learn VERB cana-616 6 17 rates rate NOUN cana-616 6 18 and and CCONJ cana-616 6 19 decision decision NOUN cana-616 6 20 boundary boundary ADJ cana-616 6 21 formations formation NOUN cana-616 6 22 . . PUNCT cana-616 7 1 this this DET cana-616 7 2 paper paper NOUN cana-616 7 3 details detail NOUN cana-616 7 4 our our PRON cana-616 7 5 methodology methodology NOUN cana-616 7 6 , , PUNCT cana-616 7 7 experimental experimental ADJ cana-616 7 8 setup setup NOUN cana-616 7 9 , , PUNCT cana-616 7 10 and and CCONJ cana-616 7 11 statistical statistical ADJ cana-616 7 12 validations validation NOUN cana-616 7 13 , , PUNCT cana-616 7 14 highlighting highlight VERB cana-616 7 15 the the DET cana-616 7 16 benefits benefit NOUN cana-616 7 17 of of ADP cana-616 7 18 our our PRON cana-616 7 19 approach approach NOUN cana-616 7 20 . . PUNCT cana-616 8 1 our our PRON cana-616 8 2 findings finding NOUN cana-616 8 3 suggest suggest VERB cana-616 8 4 that that SCONJ cana-616 8 5 the the DET cana-616 8 6 improved improve VERB cana-616 8 7 random random ADJ cana-616 8 8 forest forest NOUN cana-616 8 9 classifier classifier NOUN cana-616 8 10 can can AUX cana-616 8 11 serve serve VERB cana-616 8 12 as as ADP cana-616 8 13 a a DET cana-616 8 14 powerful powerful ADJ cana-616 8 15 tool tool NOUN cana-616 8 16 for for ADP cana-616 8 17 veterinary veterinary ADJ cana-616 8 18 diagnostics diagnostic NOUN cana-616 8 19 and and CCONJ cana-616 8 20 may may AUX cana-616 8 21 be be AUX cana-616 8 22 adaptable adaptable ADJ cana-616 8 23 for for ADP cana-616 8 24 other other ADJ cana-616 8 25 complex complex ADJ cana-616 8 26 image image NOUN cana-616 8 27 classification classification NOUN cana-616 8 28 tasks task NOUN cana-616 8 29 . . PUNCT cana-616 9 1 keywords keyword NOUN cana-616 9 2 : : PUNCT cana-616 9 3 bayesian bayesian NOUN cana-616 9 4 optimization optimization NOUN cana-616 9 5 , , PUNCT cana-616 9 6 gradient gradient ADJ cana-616 9 7 computation computation NOUN cana-616 9 8 , , PUNCT cana-616 9 9 hessian hessian ADJ cana-616 9 10 computation computation NOUN cana-616 9 11 , , PUNCT cana-616 9 12 random random ADJ cana-616 9 13 forest forest NOUN cana-616 9 14 classifier classifier NOUN cana-616 9 15 , , PUNCT cana-616 9 16 non non ADJ cana-616 9 17 - - ADJ cana-616 9 18 linear linear ADJ cana-616 9 19 classification classification NOUN cana-616 9 20 , , PUNCT cana-616 9 21 image image NOUN cana-616 9 22 classification classification NOUN cana-616 9 23 , , PUNCT cana-616 9 24 lumpy lumpy ADJ cana-616 9 25 skin skin NOUN cana-616 9 26 disease disease NOUN cana-616 9 27 , , PUNCT cana-616 9 28 veterinary veterinary ADJ cana-616 9 29 diagnostics diagnostic NOUN cana-616 9 30 , , PUNCT cana-616 9 31 machine machine NOUN cana-616 9 32 learning learning NOUN cana-616 9 33 , , PUNCT cana-616 9 34 statistical statistical ADJ cana-616 9 35 assessment assessment NOUN cana-616 9 36 1 1 NUM cana-616 9 37 . . PUNCT cana-616 10 1 introduction introduction NOUN cana-616 10 2 : : PUNCT cana-616 10 3 integrating integrate VERB cana-616 10 4 sophisticated sophisticated ADJ cana-616 10 5 mathematical mathematical ADJ cana-616 10 6 models model NOUN cana-616 10 7 and and CCONJ cana-616 10 8 advanced advanced ADJ cana-616 10 9 optimization optimization NOUN cana-616 10 10 techniques technique NOUN cana-616 10 11 into into ADP cana-616 10 12 machine machine NOUN cana-616 10 13 learning learn VERB cana-616 10 14 algorithms algorithm NOUN cana-616 10 15 has have AUX cana-616 10 16 become become VERB cana-616 10 17 a a DET cana-616 10 18 cornerstone cornerstone NOUN cana-616 10 19 strategy strategy NOUN cana-616 10 20 in in ADP cana-616 10 21 enhancing enhance VERB cana-616 10 22 their their PRON cana-616 10 23 performance performance NOUN cana-616 10 24 , , PUNCT cana-616 10 25 particularly particularly ADV cana-616 10 26 in in ADP cana-616 10 27 complex complex ADJ cana-616 10 28 classification classification NOUN cana-616 10 29 tasks task NOUN cana-616 10 30 . . PUNCT cana-616 11 1 this this DET cana-616 11 2 approach approach NOUN cana-616 11 3 is be AUX cana-616 11 4 vividly vividly ADV cana-616 11 5 illustrated illustrate VERB cana-616 11 6 in in ADP cana-616 11 7 the the DET cana-616 11 8 development development NOUN cana-616 11 9 and and CCONJ cana-616 11 10 refinement refinement NOUN cana-616 11 11 of of ADP cana-616 11 12 random random ADJ cana-616 11 13 forest forest NOUN cana-616 11 14 ( ( PUNCT cana-616 11 15 rf rf NOUN cana-616 11 16 ) ) PUNCT cana-616 11 17 classifiers classifier NOUN cana-616 11 18 , , PUNCT cana-616 11 19 which which PRON cana-616 11 20 are be AUX cana-616 11 21 among among ADP cana-616 11 22 the the DET cana-616 11 23 most most ADV cana-616 11 24 widely widely ADV cana-616 11 25 used use VERB cana-616 11 26 and and CCONJ cana-616 11 27 robust robust ADJ cana-616 11 28 algorithms algorithm NOUN cana-616 11 29 in in ADP cana-616 11 30 the the DET cana-616 11 31 field field NOUN cana-616 11 32 of of ADP cana-616 11 33 data datum NOUN cana-616 11 34 science science NOUN cana-616 11 35 and and CCONJ cana-616 11 36 machine machine NOUN cana-616 11 37 learning learning NOUN cana-616 11 38 . . PUNCT cana-616 12 1 the the DET cana-616 12 2 essence essence NOUN cana-616 12 3 of of ADP cana-616 12 4 this this DET cana-616 12 5 integration integration NOUN cana-616 12 6 lies lie VERB cana-616 12 7 in in ADP cana-616 12 8 harnessing harness VERB cana-616 12 9 the the DET cana-616 12 10 power power NOUN cana-616 12 11 of of ADP cana-616 12 12 bayesian bayesian NOUN cana-616 12 13 optimization optimization NOUN cana-616 12 14 , , PUNCT cana-616 12 15 gradient gradient NOUN cana-616 12 16 and and CCONJ cana-616 12 17 hessian hessian ADJ cana-616 12 18 computations computation NOUN cana-616 12 19 , , PUNCT cana-616 12 20 and and CCONJ cana-616 12 21 tailored tailor VERB cana-616 12 22 performance performance NOUN cana-616 12 23 evaluation evaluation NOUN cana-616 12 24 metrics metric NOUN cana-616 12 25 to to PART cana-616 12 26 significantly significantly ADV cana-616 12 27 boost boost VERB cana-616 12 28 the the DET cana-616 12 29 accuracy accuracy NOUN cana-616 12 30 and and CCONJ cana-616 12 31 efficiency efficiency NOUN cana-616 12 32 of of ADP cana-616 12 33 rf rf NOUN cana-616 12 34 classifiers classifier NOUN cana-616 12 35 . . PUNCT cana-616 13 1 this this DET cana-616 13 2 extended extend VERB cana-616 13 3 introduction introduction NOUN cana-616 13 4 explores explore NOUN cana-616 13 5 how how SCONJ cana-616 13 6 these these DET cana-616 13 7 elements element NOUN cana-616 13 8 are be AUX cana-616 13 9 synergistically synergistically ADV cana-616 13 10 combined combine VERB cana-616 13 11 to to PART cana-616 13 12 optimize optimize VERB cana-616 13 13 random random ADJ cana-616 13 14 forest forest NOUN cana-616 13 15 classifiers classifier NOUN cana-616 13 16 for for ADP cana-616 13 17 challenging challenge VERB cana-616 13 18 applications application NOUN cana-616 13 19 such such ADJ cana-616 13 20 as as ADP cana-616 13 21 image image NOUN cana-616 13 22 - - PUNCT cana-616 13 23 based base VERB cana-616 13 24 disease disease NOUN cana-616 13 25 detection detection NOUN cana-616 13 26 in in ADP cana-616 13 27 veterinary veterinary ADJ cana-616 13 28 medicine medicine NOUN cana-616 13 29 . . PUNCT cana-616 14 1 [ [ X cana-616 14 2 1 1 NUM cana-616 14 3 - - SYM cana-616 14 4 5 5 NUM cana-616 14 5 ] ] PUNCT cana-616 14 6 . . PUNCT cana-616 15 1 the the DET cana-616 15 2 random random ADJ cana-616 15 3 forest forest NOUN cana-616 15 4 algorithm algorithm NOUN cana-616 15 5 , , PUNCT cana-616 15 6 fundamentally fundamentally ADV cana-616 15 7 an an DET cana-616 15 8 ensemble ensemble NOUN cana-616 15 9 of of ADP cana-616 15 10 decision decision NOUN cana-616 15 11 trees tree NOUN cana-616 15 12 , , PUNCT cana-616 15 13 is be AUX cana-616 15 14 traditionally traditionally ADV cana-616 15 15 valued value VERB cana-616 15 16 for for ADP cana-616 15 17 its its PRON cana-616 15 18 high high ADJ cana-616 15 19 accuracy accuracy NOUN cana-616 15 20 , , PUNCT cana-616 15 21 ease ease NOUN cana-616 15 22 of of ADP cana-616 15 23 use use NOUN cana-616 15 24 , , PUNCT cana-616 15 25 and and CCONJ cana-616 15 26 robustness robustness NOUN cana-616 15 27 to to ADP cana-616 15 28 overfitting overfitte VERB cana-616 15 29 , , PUNCT cana-616 15 30 especially especially ADV cana-616 15 31 in in ADP cana-616 15 32 the the DET cana-616 15 33 context context NOUN cana-616 15 34 of of ADP cana-616 15 35 large large ADJ cana-616 15 36 and and CCONJ cana-616 15 37 complex complex ADJ cana-616 15 38 datasets dataset NOUN cana-616 15 39 . . PUNCT cana-616 16 1 however however ADV cana-616 16 2 , , PUNCT cana-616 16 3 despite despite SCONJ cana-616 16 4 its its PRON cana-616 16 5 numerous numerous ADJ cana-616 16 6 advantages advantage NOUN cana-616 16 7 , , PUNCT cana-616 16 8 the the DET cana-616 16 9 performance performance NOUN cana-616 16 10 of of ADP cana-616 16 11 rf rf PRON cana-616 16 12 can can AUX cana-616 16 13 still still ADV cana-616 16 14 be be AUX cana-616 16 15 mailto:sunil.gupta@poornima.edu.in mailto:sunil.gupta@poornima.edu.in PROPN cana-616 16 16 communications communication NOUN cana-616 16 17 on on ADP cana-616 16 18 applied apply VERB cana-616 16 19 nonlinear nonlinear ADJ cana-616 16 20 analysis analysis NOUN cana-616 16 21 issn issn NOUN cana-616 16 22 : : PUNCT cana-616 16 23 1074 1074 NUM cana-616 16 24 - - PUNCT cana-616 16 25 133x 133x NUM cana-616 16 26 vol vol NOUN cana-616 16 27 31 31 NUM cana-616 16 28 no no NOUN cana-616 16 29 . . PUNCT cana-616 17 1 2s 2s NUM cana-616 17 2 ( ( PUNCT cana-616 17 3 2024 2024 NUM cana-616 17 4 ) ) PUNCT cana-616 17 5 119 119 NUM cana-616 17 6 https://internationalpubls.com https://internationalpubls.com NUM cana-616 17 7 limited limit VERB cana-616 17 8 by by ADP cana-616 17 9 its its PRON cana-616 17 10 hyperparameter hyperparameter NOUN cana-616 17 11 settings setting NOUN cana-616 17 12 , , PUNCT cana-616 17 13 the the DET cana-616 17 14 method method NOUN cana-616 17 15 of of ADP cana-616 17 16 handling handle VERB cana-616 17 17 high high ADJ cana-616 17 18 - - PUNCT cana-616 17 19 dimensional dimensional ADJ cana-616 17 20 spaces space NOUN cana-616 17 21 , , PUNCT cana-616 17 22 and and CCONJ cana-616 17 23 its its PRON cana-616 17 24 ability ability NOUN cana-616 17 25 to to PART cana-616 17 26 adapt adapt VERB cana-616 17 27 to to ADP cana-616 17 28 new new ADJ cana-616 17 29 or or CCONJ cana-616 17 30 evolving evolve VERB cana-616 17 31 data datum NOUN cana-616 17 32 scenarios scenario NOUN cana-616 17 33 . . PUNCT cana-616 18 1 addressing address VERB cana-616 18 2 these these DET cana-616 18 3 limitations limitation NOUN cana-616 18 4 requires require VERB cana-616 18 5 a a DET cana-616 18 6 nuanced nuanced ADJ cana-616 18 7 understanding understanding NOUN cana-616 18 8 of of ADP cana-616 18 9 both both CCONJ cana-616 18 10 the the DET cana-616 18 11 algorithm algorithm NOUN cana-616 18 12 itself itself PRON cana-616 18 13 and and CCONJ cana-616 18 14 the the DET cana-616 18 15 mathematical mathematical ADJ cana-616 18 16 tools tool NOUN cana-616 18 17 that that PRON cana-616 18 18 can can AUX cana-616 18 19 be be AUX cana-616 18 20 used use VERB cana-616 18 21 to to PART cana-616 18 22 refine refine VERB cana-616 18 23 it it PRON cana-616 18 24 [ [ X cana-616 18 25 68 68 NUM cana-616 18 26 ] ] PUNCT cana-616 18 27 . . PUNCT cana-616 19 1 hyperparameter hyperparameter PROPN cana-616 19 2 tuning tuning NOUN cana-616 19 3 , , PUNCT cana-616 19 4 model model NOUN cana-616 19 5 complexity complexity NOUN cana-616 19 6 control control NOUN cana-616 19 7 , , PUNCT cana-616 19 8 and and CCONJ cana-616 19 9 performance performance NOUN cana-616 19 10 optimization optimization NOUN cana-616 19 11 are be AUX cana-616 19 12 critical critical ADJ cana-616 19 13 areas area NOUN cana-616 19 14 where where SCONJ cana-616 19 15 advanced advanced ADJ cana-616 19 16 mathematical mathematical ADJ cana-616 19 17 concepts concept NOUN cana-616 19 18 can can AUX cana-616 19 19 play play VERB cana-616 19 20 a a DET cana-616 19 21 pivotal pivotal ADJ cana-616 19 22 role role NOUN cana-616 19 23 . . PUNCT cana-616 20 1 by by ADP cana-616 20 2 integrating integrate VERB cana-616 20 3 bayesian bayesian NOUN cana-616 20 4 optimization optimization NOUN cana-616 20 5 , , PUNCT cana-616 20 6 we we PRON cana-616 20 7 can can AUX cana-616 20 8 streamline streamline VERB cana-616 20 9 the the DET cana-616 20 10 process process NOUN cana-616 20 11 of of ADP cana-616 20 12 hyperparameter hyperparameter NOUN cana-616 20 13 selection selection NOUN cana-616 20 14 , , PUNCT cana-616 20 15 significantly significantly ADV cana-616 20 16 reducing reduce VERB cana-616 20 17 the the DET cana-616 20 18 computational computational ADJ cana-616 20 19 overhead overhead NOUN cana-616 20 20 associated associate VERB cana-616 20 21 with with ADP cana-616 20 22 traditional traditional ADJ cana-616 20 23 grid grid NOUN cana-616 20 24 or or CCONJ cana-616 20 25 random random ADJ cana-616 20 26 search search NOUN cana-616 20 27 methods method NOUN cana-616 20 28 . . PUNCT cana-616 21 1 similarly similarly ADV cana-616 21 2 , , PUNCT cana-616 21 3 employing employ VERB cana-616 21 4 gradient gradient NOUN cana-616 21 5 and and CCONJ cana-616 21 6 hessian hessian ADJ cana-616 21 7 information information NOUN cana-616 21 8 helps help VERB cana-616 21 9 in in ADP cana-616 21 10 fine fine ADV cana-616 21 11 - - PUNCT cana-616 21 12 tuning tune VERB cana-616 21 13 the the DET cana-616 21 14 model model NOUN cana-616 21 15 to to PART cana-616 21 16 better well ADV cana-616 21 17 navigate navigate VERB cana-616 21 18 the the DET cana-616 21 19 parameter parameter NOUN cana-616 21 20 space space NOUN cana-616 21 21 , , PUNCT cana-616 21 22 enhancing enhance VERB cana-616 21 23 the the DET cana-616 21 24 learning learning NOUN cana-616 21 25 process process NOUN cana-616 21 26 at at ADP cana-616 21 27 a a DET cana-616 21 28 granular granular ADJ cana-616 21 29 level level NOUN cana-616 21 30 [ [ X cana-616 21 31 3 3 NUM cana-616 21 32 - - SYM cana-616 21 33 9 9 NUM cana-616 21 34 ] ] PUNCT cana-616 21 35 . . PUNCT cana-616 22 1 diagnosis diagnosis NOUN cana-616 22 2 relies rely VERB cana-616 22 3 on on ADP cana-616 22 4 clinical clinical ADJ cana-616 22 5 signs sign NOUN cana-616 22 6 and and CCONJ cana-616 22 7 laboratory laboratory NOUN cana-616 22 8 testing testing NOUN cana-616 22 9 , , PUNCT cana-616 22 10 with with ADP cana-616 22 11 samples sample NOUN cana-616 22 12 of of ADP cana-616 22 13 blood blood NOUN cana-616 22 14 , , PUNCT cana-616 22 15 skin skin NOUN cana-616 22 16 nodules nodule NOUN cana-616 22 17 , , PUNCT cana-616 22 18 or or CCONJ cana-616 22 19 other other ADJ cana-616 22 20 tissues tissue NOUN cana-616 22 21 collected collect VERB cana-616 22 22 for for ADP cana-616 22 23 pcr pcr NOUN cana-616 22 24 or or CCONJ cana-616 22 25 elisa elisa VERB cana-616 22 26 analysis analysis NOUN cana-616 22 27 . . PUNCT cana-616 23 1 long long ADJ cana-616 23 2 - - PUNCT cana-616 23 3 term term NOUN cana-616 23 4 effects effect NOUN cana-616 23 5 may may AUX cana-616 23 6 include include VERB cana-616 23 7 abnormalities abnormality NOUN cana-616 23 8 , , PUNCT cana-616 23 9 reduced reduce VERB cana-616 23 10 milk milk NOUN cana-616 23 11 production production NOUN cana-616 23 12 , , PUNCT cana-616 23 13 growth growth NOUN cana-616 23 14 retardation retardation NOUN cana-616 23 15 , , PUNCT cana-616 23 16 sterility sterility NOUN cana-616 23 17 , , PUNCT cana-616 23 18 stillbirth stillbirth NOUN cana-616 23 19 , , PUNCT cana-616 23 20 and and CCONJ cana-616 23 21 , , PUNCT cana-616 23 22 in in ADP cana-616 23 23 severe severe ADJ cana-616 23 24 cases case NOUN cana-616 23 25 , , PUNCT cana-616 23 26 death death NOUN cana-616 23 27 . . PUNCT cana-616 24 1 fever fever NOUN cana-616 24 2 usually usually ADV cana-616 24 3 manifests manifest VERB cana-616 24 4 around around ADP cana-616 24 5 one one NUM cana-616 24 6 - - PUNCT cana-616 24 7 week week NOUN cana-616 24 8 post post NOUN cana-616 24 9 - - NOUN cana-616 24 10 infection infection NOUN cana-616 24 11 [ [ X cana-616 24 12 7 7 NUM cana-616 24 13 - - SYM cana-616 24 14 10 10 NUM cana-616 24 15 ] ] PUNCT cana-616 24 16 . . PUNCT cana-616 25 1 bayesian bayesian NOUN cana-616 25 2 optimization optimization NOUN cana-616 25 3 and and CCONJ cana-616 25 4 random random ADJ cana-616 25 5 forest forest NOUN cana-616 25 6 bayesian bayesian NOUN cana-616 25 7 optimization optimization NOUN cana-616 25 8 ( ( PUNCT cana-616 25 9 bo bo PROPN cana-616 25 10 ) ) PUNCT cana-616 25 11 is be AUX cana-616 25 12 a a DET cana-616 25 13 strategy strategy NOUN cana-616 25 14 that that PRON cana-616 25 15 uses use VERB cana-616 25 16 a a DET cana-616 25 17 probabilistic probabilistic ADJ cana-616 25 18 model model NOUN cana-616 25 19 to to PART cana-616 25 20 guide guide VERB cana-616 25 21 the the DET cana-616 25 22 search search NOUN cana-616 25 23 for for ADP cana-616 25 24 the the DET cana-616 25 25 optimal optimal ADJ cana-616 25 26 parameters parameter NOUN cana-616 25 27 of of ADP cana-616 25 28 a a DET cana-616 25 29 function function NOUN cana-616 25 30 . . PUNCT cana-616 26 1 in in ADP cana-616 26 2 the the DET cana-616 26 3 context context NOUN cana-616 26 4 of of ADP cana-616 26 5 rf rf NOUN cana-616 26 6 , , PUNCT cana-616 26 7 bo bo PROPN cana-616 26 8 can can AUX cana-616 26 9 be be AUX cana-616 26 10 employed employ VERB cana-616 26 11 to to PART cana-616 26 12 find find VERB cana-616 26 13 the the DET cana-616 26 14 best good ADJ cana-616 26 15 set set NOUN cana-616 26 16 of of ADP cana-616 26 17 hyperparameters hyperparameter NOUN cana-616 26 18 , , PUNCT cana-616 26 19 such such ADJ cana-616 26 20 as as ADP cana-616 26 21 the the DET cana-616 26 22 number number NOUN cana-616 26 23 of of ADP cana-616 26 24 trees tree NOUN cana-616 26 25 in in ADP cana-616 26 26 the the DET cana-616 26 27 forest forest NOUN cana-616 26 28 , , PUNCT cana-616 26 29 the the DET cana-616 26 30 depth depth NOUN cana-616 26 31 of of ADP cana-616 26 32 each each DET cana-616 26 33 tree tree NOUN cana-616 26 34 , , PUNCT cana-616 26 35 or or CCONJ cana-616 26 36 the the DET cana-616 26 37 minimum minimum ADJ cana-616 26 38 number number NOUN cana-616 26 39 of of ADP cana-616 26 40 samples sample NOUN cana-616 26 41 required require VERB cana-616 26 42 to to PART cana-616 26 43 split split VERB cana-616 26 44 a a DET cana-616 26 45 node node NOUN cana-616 26 46 . . PUNCT cana-616 27 1 this this DET cana-616 27 2 process process NOUN cana-616 27 3 involves involve VERB cana-616 27 4 constructing construct VERB cana-616 27 5 a a DET cana-616 27 6 surrogate surrogate ADJ cana-616 27 7 model model NOUN cana-616 27 8 , , PUNCT cana-616 27 9 typically typically ADV cana-616 27 10 a a DET cana-616 27 11 gaussian gaussian ADJ cana-616 27 12 process process NOUN cana-616 27 13 ( ( PUNCT cana-616 27 14 gp gp NOUN cana-616 27 15 ) ) PUNCT cana-616 27 16 , , PUNCT cana-616 27 17 which which PRON cana-616 27 18 estimates estimate VERB cana-616 27 19 the the DET cana-616 27 20 performance performance NOUN cana-616 27 21 of of ADP cana-616 27 22 the the DET cana-616 27 23 rf rf NOUN cana-616 27 24 as as ADP cana-616 27 25 a a DET cana-616 27 26 function function NOUN cana-616 27 27 of of ADP cana-616 27 28 its its PRON cana-616 27 29 hyperparameters hyperparameter NOUN cana-616 27 30 . . PUNCT cana-616 28 1 the the DET cana-616 28 2 surrogate surrogate NOUN cana-616 28 3 is be AUX cana-616 28 4 then then ADV cana-616 28 5 used use VERB cana-616 28 6 to to PART cana-616 28 7 calculate calculate VERB cana-616 28 8 acquisition acquisition NOUN cana-616 28 9 functions function NOUN cana-616 28 10 , , PUNCT cana-616 28 11 like like ADP cana-616 28 12 expected expect VERB cana-616 28 13 improvement improvement NOUN cana-616 28 14 , , PUNCT cana-616 28 15 which which PRON cana-616 28 16 provide provide VERB cana-616 28 17 a a DET cana-616 28 18 balance balance NOUN cana-616 28 19 between between ADP cana-616 28 20 exploring explore VERB cana-616 28 21 new new ADJ cana-616 28 22 parameter parameter NOUN cana-616 28 23 settings setting NOUN cana-616 28 24 and and CCONJ cana-616 28 25 exploiting exploit VERB cana-616 28 26 known know VERB cana-616 28 27 configurations configuration NOUN cana-616 28 28 that that PRON cana-616 28 29 perform perform VERB cana-616 28 30 well well INTJ cana-616 29 1 [ [ X cana-616 29 2 22 22 NUM cana-616 29 3 ] ] PUNCT cana-616 29 4 . . PUNCT cana-616 30 1 gradient gradient NOUN cana-616 30 2 and and CCONJ cana-616 30 3 hessian hessian ADJ cana-616 30 4 computations computation NOUN cana-616 30 5 while while SCONJ cana-616 30 6 random random ADJ cana-616 30 7 forests forest NOUN cana-616 30 8 do do AUX cana-616 30 9 not not PART cana-616 30 10 inherently inherently ADV cana-616 30 11 utilize utilize VERB cana-616 30 12 gradient gradient ADJ cana-616 30 13 information information NOUN cana-616 30 14 as as ADP cana-616 30 15 methods method NOUN cana-616 30 16 like like ADP cana-616 30 17 gradient gradient NOUN cana-616 30 18 boosting boosting NOUN cana-616 30 19 , , PUNCT cana-616 30 20 integrating integrate VERB cana-616 30 21 this this DET cana-616 30 22 aspect aspect NOUN cana-616 30 23 can can AUX cana-616 30 24 be be AUX cana-616 30 25 pivotal pivotal ADJ cana-616 30 26 when when SCONJ cana-616 30 27 rf rf PRON cana-616 30 28 is be AUX cana-616 30 29 used use VERB cana-616 30 30 as as ADP cana-616 30 31 part part NOUN cana-616 30 32 of of ADP cana-616 30 33 a a DET cana-616 30 34 larger large ADJ cana-616 30 35 prediction prediction NOUN cana-616 30 36 framework framework NOUN cana-616 30 37 that that PRON cana-616 30 38 includes include VERB cana-616 30 39 gradient gradient NOUN cana-616 30 40 - - PUNCT cana-616 30 41 based base VERB cana-616 30 42 optimization optimization NOUN cana-616 30 43 tasks task NOUN cana-616 30 44 . . PUNCT cana-616 31 1 for for ADP cana-616 31 2 example example NOUN cana-616 31 3 , , PUNCT cana-616 31 4 gradients gradient NOUN cana-616 31 5 and and CCONJ cana-616 31 6 hessians hessian NOUN cana-616 31 7 can can AUX cana-616 31 8 be be AUX cana-616 31 9 crucial crucial ADJ cana-616 31 10 in in ADP cana-616 31 11 fine fine ADV cana-616 31 12 - - PUNCT cana-616 31 13 tuning tune VERB cana-616 31 14 algorithms algorithm NOUN cana-616 31 15 where where SCONJ cana-616 31 16 rf rf NOUN cana-616 31 17 predictions prediction NOUN cana-616 31 18 are be AUX cana-616 31 19 a a DET cana-616 31 20 component component NOUN cana-616 31 21 of of ADP cana-616 31 22 the the DET cana-616 31 23 objective objective ADJ cana-616 31 24 function function NOUN cana-616 31 25 to to PART cana-616 31 26 be be AUX cana-616 31 27 optimized optimize VERB cana-616 31 28 . . PUNCT cana-616 32 1 such such ADJ cana-616 32 2 applications application NOUN cana-616 32 3 are be AUX cana-616 32 4 prevalent prevalent ADJ cana-616 32 5 in in ADP cana-616 32 6 complex complex ADJ cana-616 32 7 systems system NOUN cana-616 32 8 modeling modeling NOUN cana-616 32 9 and and CCONJ cana-616 32 10 reinforcement reinforcement NOUN cana-616 32 11 learning learning NOUN cana-616 32 12 scenarios scenario NOUN cana-616 32 13 , , PUNCT cana-616 32 14 where where SCONJ cana-616 32 15 an an DET cana-616 32 16 understanding understanding NOUN cana-616 32 17 of of ADP cana-616 32 18 how how SCONJ cana-616 32 19 changes change NOUN cana-616 32 20 in in ADP cana-616 32 21 input input NOUN cana-616 32 22 data datum NOUN cana-616 32 23 influence influence NOUN cana-616 32 24 predicted predict VERB cana-616 32 25 outcomes outcome NOUN cana-616 32 26 is be AUX cana-616 32 27 crucial crucial ADJ cana-616 32 28 [ [ X cana-616 32 29 23 23 NUM cana-616 32 30 - - SYM cana-616 32 31 26 26 NUM cana-616 32 32 ] ] PUNCT cana-616 32 33 . . PUNCT cana-616 33 1 communications communication NOUN cana-616 33 2 on on ADP cana-616 33 3 applied apply VERB cana-616 33 4 nonlinear nonlinear ADJ cana-616 33 5 analysis analysis NOUN cana-616 33 6 issn issn NOUN cana-616 33 7 : : PUNCT cana-616 33 8 1074 1074 NUM cana-616 33 9 - - PUNCT cana-616 33 10 133x 133x NUM cana-616 33 11 vol vol NOUN cana-616 33 12 31 31 NUM cana-616 33 13 no no NOUN cana-616 33 14 . . PUNCT cana-616 34 1 2s 2s NUM cana-616 34 2 ( ( PUNCT cana-616 34 3 2024 2024 NUM cana-616 34 4 ) ) PUNCT cana-616 34 5 120 120 NUM cana-616 34 6 https://internationalpubls.com https://internationalpubls.com X cana-616 34 7 figure1 figure1 NUM cana-616 34 8 : : PUNCT cana-616 34 9 hyperparameter hyperparameter NOUN cana-616 34 10 optimization optimization NOUN cana-616 34 11 landscape landscape NOUN cana-616 34 12 figure figure NOUN cana-616 34 13 1 1 NUM cana-616 34 14 illustrates illustrate VERB cana-616 34 15 the the DET cana-616 34 16 performance performance NOUN cana-616 34 17 of of ADP cana-616 34 18 a a DET cana-616 34 19 random random ADJ cana-616 34 20 forest forest NOUN cana-616 34 21 classifier classifier NOUN cana-616 34 22 as as ADP cana-616 34 23 a a DET cana-616 34 24 function function NOUN cana-616 34 25 of of ADP cana-616 34 26 two two NUM cana-616 34 27 key key ADJ cana-616 34 28 hyperparameters hyperparameter NOUN cana-616 34 29 : : PUNCT cana-616 34 30 the the DET cana-616 34 31 number number NOUN cana-616 34 32 of of ADP cana-616 34 33 trees tree NOUN cana-616 34 34 and and CCONJ cana-616 34 35 the the DET cana-616 34 36 depth depth NOUN cana-616 34 37 of of ADP cana-616 34 38 each each DET cana-616 34 39 tree tree NOUN cana-616 34 40 . . PUNCT cana-616 35 1 figure figure VERB cana-616 35 2 2 2 NUM cana-616 35 3 : : PUNCT cana-616 35 4 convergence convergence NOUN cana-616 35 5 of of ADP cana-616 35 6 bayesian bayesian NOUN cana-616 35 7 optimization optimization NOUN cana-616 35 8 to to PART cana-616 35 9 enhance enhance VERB cana-616 35 10 detection detection NOUN cana-616 35 11 and and CCONJ cana-616 35 12 monitoring monitoring NOUN cana-616 35 13 , , PUNCT cana-616 35 14 the the DET cana-616 35 15 convergence convergence NOUN cana-616 35 16 of of ADP cana-616 35 17 bayesian bayesian NOUN cana-616 35 18 optimization optimization NOUN cana-616 35 19 plot plot NOUN cana-616 35 20 illustrates illustrate VERB cana-616 35 21 the the DET cana-616 35 22 performance performance NOUN cana-616 35 23 improvement improvement NOUN cana-616 35 24 of of ADP cana-616 35 25 bayesian bayesian NOUN cana-616 35 26 optimization optimization NOUN cana-616 35 27 in in ADP cana-616 35 28 tuning tune VERB cana-616 35 29 hyperparameters hyperparameter NOUN cana-616 35 30 over over ADP cana-616 35 31 successive successive ADJ cana-616 35 32 iterations iteration NOUN cana-616 35 33 for for ADP cana-616 35 34 a a DET cana-616 35 35 random random ADJ cana-616 35 36 forest forest NOUN cana-616 35 37 classifier classifier NOUN cana-616 36 1 [ [ X cana-616 36 2 1 1 NUM cana-616 36 3 - - SYM cana-616 36 4 8 8 NUM cana-616 36 5 ] ] PUNCT cana-616 36 6 . . PUNCT cana-616 37 1 random random ADJ cana-616 37 2 forest forest NOUN cana-616 37 3 classifier classifier NOUN cana-616 37 4 basic basic ADJ cana-616 37 5 algorithm algorithm NOUN cana-616 37 6 entropy entropy NOUN cana-616 37 7 ( ( PUNCT cana-616 37 8 𝐻 𝐻 NOUN cana-616 37 9 ) ) PUNCT cana-616 37 10 communications communication NOUN cana-616 37 11 on on ADP cana-616 37 12 applied apply VERB cana-616 37 13 nonlinear nonlinear ADJ cana-616 37 14 analysis analysis NOUN cana-616 37 15 issn issn NOUN cana-616 37 16 : : PUNCT cana-616 37 17 1074 1074 NUM cana-616 37 18 - - PUNCT cana-616 37 19 133x 133x NUM cana-616 37 20 vol vol NOUN cana-616 37 21 31 31 NUM cana-616 37 22 no no NOUN cana-616 37 23 . . PUNCT cana-616 38 1 2s 2s NUM cana-616 38 2 ( ( PUNCT cana-616 38 3 2024 2024 NUM cana-616 38 4 ) ) PUNCT cana-616 38 5 121 121 NUM cana-616 38 6 https://internationalpubls.com https://internationalpubls.com X cana-616 38 7 𝐻(𝑆 𝐻(𝑆 NOUN cana-616 38 8 ) ) PUNCT cana-616 38 9 βˆ’ βˆ’ PROPN cana-616 38 10 βˆ’βˆ‘ βˆ’βˆ‘ PROPN cana-616 38 11 β€Š β€Š SPACE cana-616 38 12 𝑐 𝑐 PROPN cana-616 38 13 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-616 38 14 𝑝𝑖log2⁑ 𝑝𝑖log2⁑ NOUN cana-616 38 15 𝑝𝑖 𝑝𝑖 NOUN cana-616 38 16 ( ( PUNCT cana-616 38 17 1 1 NUM cana-616 38 18 ) ) PUNCT cana-616 38 19 where where SCONJ cana-616 38 20 𝑝𝑖 𝑝𝑖 NOUN cana-616 38 21 is be AUX cana-616 38 22 the the DET cana-616 38 23 proportion proportion NOUN cana-616 38 24 of of ADP cana-616 38 25 class class NOUN cana-616 38 26 𝑖 𝑖 NOUN cana-616 38 27 instances instance NOUN cana-616 38 28 within within ADP cana-616 38 29 dataset dataset NOUN cana-616 38 30 𝑆. 𝑆. NOUN cana-616 38 31 information information NOUN cana-616 38 32 gain gain NOUN cana-616 38 33 ( ( PUNCT cana-616 38 34 ig ig NOUN cana-616 38 35 ) ) PUNCT cana-616 38 36 𝐼𝐺(𝑆 𝐼𝐺(𝑆 PROPN cana-616 38 37 , , PUNCT cana-616 38 38 𝐴 𝐴 PROPN cana-616 38 39 ) ) PUNCT cana-616 38 40 βˆ’ βˆ’ PROPN cana-616 38 41 𝐻(𝑆 𝐻(𝑆 NOUN cana-616 38 42 ) ) PUNCT cana-616 38 43 βˆ’ βˆ’ PROPN cana-616 38 44 βˆ‘ βˆ‘ ADP cana-616 38 45 β€Š β€Š SPACE cana-616 38 46 π‘‘βˆˆπ‘‡ π‘‘βˆˆπ‘‡ NOUN cana-616 38 47 |𝑆𝑑| |𝑆𝑑| VERB cana-616 38 48 |𝑆| |𝑆| VERB cana-616 38 49 𝐻(𝑆𝑑 𝐻(𝑆𝑑 NOUN cana-616 38 50 ) ) PUNCT cana-616 38 51 ( ( PUNCT cana-616 38 52 2 2 X cana-616 38 53 ) ) PUNCT cana-616 38 54 where where SCONJ cana-616 38 55 𝐴 𝐴 PROPN cana-616 38 56 is be AUX cana-616 38 57 the the DET cana-616 38 58 attribute attribute NOUN cana-616 38 59 , , PUNCT cana-616 38 60 𝑇 𝑇 PROPN cana-616 38 61 are be AUX cana-616 38 62 the the DET cana-616 38 63 subsets subset NOUN cana-616 38 64 of of ADP cana-616 38 65 𝑆 𝑆 PROPN cana-616 38 66 split split VERB cana-616 38 67 by by ADP cana-616 38 68 attribute attribute NOUN cana-616 38 69 𝐴 𝐴 PROPN cana-616 38 70 , , PUNCT cana-616 38 71 and and CCONJ cana-616 38 72 |𝑆𝑑| |𝑆𝑑| NOUN cana-616 38 73 is be AUX cana-616 38 74 the the DET cana-616 38 75 size size NOUN cana-616 38 76 of of ADP cana-616 38 77 subset subset NOUN cana-616 38 78 𝑑. 𝑑. PROPN cana-616 38 79 gini gini PROPN cana-616 38 80 impurity impurity NOUN cana-616 38 81 ( ( PUNCT cana-616 38 82 g g NOUN cana-616 38 83 ) ) PUNCT cana-616 38 84 𝐺(𝑆 𝐺(𝑆 NOUN cana-616 38 85 ) ) PUNCT cana-616 39 1 βˆ’ βˆ’ PROPN cana-616 39 2 1 1 NUM cana-616 39 3 βˆ’ βˆ’ NOUN cana-616 39 4 βˆ‘ βˆ‘ PROPN cana-616 39 5 β€Š β€Š SPACE cana-616 39 6 𝑐 𝑐 PROPN cana-616 39 7 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-616 39 8 𝑝𝑖 𝑝𝑖 PROPN cana-616 39 9 2 2 NUM cana-616 39 10 ( ( PUNCT cana-616 39 11 3 3 NUM cana-616 39 12 ) ) PUNCT cana-616 39 13 bayesian bayesian NOUN cana-616 39 14 optimization optimization NOUN cana-616 39 15 bayesian bayesian NOUN cana-616 39 16 posterior posterior ADJ cana-616 39 17 probability probability NOUN cana-616 39 18 update update NOUN cana-616 39 19 𝑝(πœƒ 𝑝(πœƒ PROPN cana-616 39 20 ∣ ∣ PROPN cana-616 39 21 𝐷 𝐷 NOUN cana-616 39 22 ) ) PUNCT cana-616 39 23 ∝ ∝ PROPN cana-616 39 24 𝑝(𝐷 𝑝(𝐷 PROPN cana-616 39 25 ∣ ∣ VERB cana-616 39 26 πœƒ)𝑝(πœƒ πœƒ)𝑝(πœƒ NOUN cana-616 39 27 ) ) PUNCT cana-616 39 28 ( ( PUNCT cana-616 39 29 4 4 X cana-616 39 30 ) ) PUNCT cana-616 39 31 where where SCONJ cana-616 39 32 πœƒ πœƒ PRON cana-616 39 33 represents represent VERB cana-616 39 34 parameters parameter NOUN cana-616 39 35 and and CCONJ cana-616 39 36 𝐷 𝐷 PROPN cana-616 39 37 is be AUX cana-616 39 38 the the DET cana-616 39 39 data datum NOUN cana-616 39 40 . . PUNCT cana-616 40 1 gaussian gaussian ADJ cana-616 40 2 process process NOUN cana-616 40 3 regression regression NOUN cana-616 40 4 mean mean NOUN cana-616 40 5 function function NOUN cana-616 40 6 : : PUNCT cana-616 40 7 π‘š(π‘₯ π‘š(π‘₯ NOUN cana-616 40 8 ) ) PUNCT cana-616 40 9 βˆ’ βˆ’ NOUN cana-616 40 10 𝔼[𝑓(π‘₯ 𝔼[𝑓(π‘₯ NOUN cana-616 40 11 ) ) PUNCT cana-616 40 12 ] ] PUNCT cana-616 40 13 ( ( PUNCT cana-616 40 14 5 5 X cana-616 40 15 ) ) PUNCT cana-616 40 16 covariance covariance NOUN cana-616 40 17 function function NOUN cana-616 40 18 : : PUNCT cana-616 40 19 π‘˜(π‘₯ π‘˜(π‘₯ PROPN cana-616 40 20 , , PUNCT cana-616 40 21 π‘₯β€² π‘₯β€² NUM cana-616 40 22 ) ) PUNCT cana-616 41 1 βˆ’ βˆ’ ADP cana-616 41 2 𝔼[(𝑓(π‘₯ 𝔼[(𝑓(π‘₯ NOUN cana-616 41 3 ) ) PUNCT cana-616 41 4 βˆ’ βˆ’ PROPN cana-616 42 1 π‘š(π‘₯))(𝑓(π‘₯β€² π‘š(π‘₯))(𝑓(π‘₯β€² NUM cana-616 42 2 ) ) PUNCT cana-616 43 1 βˆ’ βˆ’ PROPN cana-616 43 2 π‘š(π‘₯β€² π‘š(π‘₯β€² NUM cana-616 43 3 ) ) PUNCT cana-616 43 4 ) ) PUNCT cana-616 43 5 ] ] PUNCT cana-616 44 1 ( ( PUNCT cana-616 44 2 6 6 X cana-616 44 3 ) ) PUNCT cana-616 44 4 gradient gradient NOUN cana-616 44 5 and and CCONJ cana-616 44 6 hessian hessian ADJ cana-616 44 7 computations computation NOUN cana-616 44 8 gradient gradient ADJ cana-616 44 9 calculation calculation NOUN cana-616 44 10 for for ADP cana-616 44 11 a a DET cana-616 44 12 function function NOUN cana-616 44 13 𝐿(πœƒ 𝐿(πœƒ PROPN cana-616 44 14 ) ) PUNCT cana-616 44 15 : : PUNCT cana-616 44 16 βˆ‡πΏ(πœƒ βˆ‡πΏ(πœƒ X cana-616 44 17 ) ) PUNCT cana-616 44 18 βˆ’ βˆ’ PROPN cana-616 45 1 ( ( PUNCT cana-616 45 2 βˆ‚πΏ βˆ‚πΏ PROPN cana-616 45 3 βˆ‚πœƒ1 βˆ‚πœƒ1 NOUN cana-616 45 4 , , PUNCT cana-616 45 5 … … PUNCT cana-616 45 6 , , PUNCT cana-616 45 7 βˆ‚πΏ βˆ‚πΏ PROPN cana-616 45 8 βˆ‚πœƒπ‘› βˆ‚πœƒπ‘› NOUN cana-616 45 9 ) ) PUNCT cana-616 45 10 𝑇 𝑇 PROPN cana-616 45 11 ( ( PUNCT cana-616 45 12 7 7 NUM cana-616 45 13 ) ) PUNCT cana-616 45 14 hessian hessian ADJ cana-616 45 15 matrix matrix NOUN cana-616 45 16 𝐻(𝐿)(πœƒ 𝐻(𝐿)(πœƒ NOUN cana-616 45 17 ) ) PUNCT cana-616 45 18 βˆ’ βˆ’ PROPN cana-616 45 19 [ [ PUNCT cana-616 45 20 βˆ‚ βˆ‚ NUM cana-616 45 21 οΏ½ οΏ½ PROPN cana-616 45 22 Μ‚ Μ‚ VERB cana-616 45 23 οΏ½ οΏ½ NOUN cana-616 45 24 2𝐿 2𝐿 NOUN cana-616 45 25 βˆ‚πœƒπ‘– βˆ‚πœƒπ‘– VERB cana-616 45 26 βˆ‚πœƒπ‘– βˆ‚πœƒπ‘– PROPN cana-616 45 27 ] ] PUNCT cana-616 46 1 𝑖,𝑗 𝑖,𝑗 X cana-616 47 1 ( ( PUNCT cana-616 47 2 8) 8) NUM cana-616 47 3 hyperparameter hyperparameter NOUN cana-616 47 4 tuning tune VERB cana-616 47 5 gradient gradient ADJ cana-616 47 6 descent descent NOUN cana-616 47 7 for for ADP cana-616 47 8 hyperparameter hyperparameter NOUN cana-616 47 9 πœ† πœ† PRON cana-616 47 10 πœ†(𝑛𝑒𝑀 πœ†(𝑛𝑒𝑀 PROPN cana-616 47 11 ) ) PUNCT cana-616 47 12 βˆ’ βˆ’ PROPN cana-616 48 1 πœ†(π‘Žπ‘™π‘‘ πœ†(π‘Žπ‘™π‘‘ ADJ cana-616 48 2 ) ) PUNCT cana-616 48 3 βˆ’ βˆ’ PROPN cana-616 49 1 𝛼 𝛼 PRON cana-616 49 2 βˆ‚πΏ βˆ‚πΏ PROPN cana-616 49 3 βˆ‚πœ† βˆ‚πœ† PROPN cana-616 49 4 ( ( PUNCT cana-616 49 5 9 9 NUM cana-616 49 6 ) ) PUNCT cana-616 49 7 where where SCONJ cana-616 49 8 𝛼 𝛼 NOUN cana-616 49 9 is be AUX cana-616 49 10 the the DET cana-616 49 11 learning learning NOUN cana-616 49 12 rate rate NOUN cana-616 49 13 . . PUNCT cana-616 50 1 learning learn VERB cana-616 50 2 rate rate NOUN cana-616 50 3 adjustment adjustment NOUN cana-616 50 4 𝛼(new 𝛼(new NOUN cana-616 50 5 ) ) PUNCT cana-616 50 6 βˆ’ βˆ’ PROPN cana-616 51 1 𝛼(π‘œπ‘™π‘‘ 𝛼(π‘œπ‘™π‘‘ PROPN cana-616 51 2 ) ) PUNCT cana-616 51 3 β‹… β‹… PROPN cana-616 51 4 decay_factor decay_factor NOUN cana-616 51 5 ( ( PUNCT cana-616 51 6 10 10 NUM cana-616 51 7 ) ) PUNCT cana-616 51 8 communications communication NOUN cana-616 51 9 on on ADP cana-616 51 10 applied apply VERB cana-616 51 11 nonlinear nonlinear ADJ cana-616 51 12 analysis analysis NOUN cana-616 51 13 issn issn NOUN cana-616 51 14 : : PUNCT cana-616 51 15 1074 1074 NUM cana-616 51 16 - - PUNCT cana-616 51 17 133x 133x NUM cana-616 51 18 vol vol NOUN cana-616 51 19 31 31 NUM cana-616 51 20 no no NOUN cana-616 51 21 . . PUNCT cana-616 52 1 2s 2s NUM cana-616 52 2 ( ( PUNCT cana-616 52 3 2024 2024 NUM cana-616 52 4 ) ) PUNCT cana-616 52 5 122 122 NUM cana-616 52 6 https://internationalpubls.com https://internationalpubls.com X cana-616 52 7 these these DET cana-616 52 8 equations equation NOUN cana-616 52 9 cover cover VERB cana-616 52 10 the the DET cana-616 52 11 primary primary ADJ cana-616 52 12 mathematical mathematical ADJ cana-616 52 13 operations operation NOUN cana-616 52 14 within within ADP cana-616 52 15 the the DET cana-616 52 16 frameworks framework NOUN cana-616 52 17 of of ADP cana-616 52 18 random random ADJ cana-616 52 19 forest forest NOUN cana-616 52 20 classification classification NOUN cana-616 52 21 and and CCONJ cana-616 52 22 bayesian bayesian NOUN cana-616 52 23 optimization optimization NOUN cana-616 52 24 , , PUNCT cana-616 52 25 tailored tailor VERB cana-616 52 26 specifically specifically ADV cana-616 52 27 for for ADP cana-616 52 28 enhancing enhance VERB cana-616 52 29 performance performance NOUN cana-616 52 30 and and CCONJ cana-616 52 31 computational computational ADJ cana-616 52 32 efficiency efficiency NOUN cana-616 52 33 in in ADP cana-616 52 34 complex complex ADJ cana-616 52 35 machine machine NOUN cana-616 52 36 learning learning NOUN cana-616 52 37 tasks task NOUN cana-616 52 38 . . PUNCT cana-616 53 1 each each DET cana-616 53 2 equation equation NOUN cana-616 53 3 serves serve VERB cana-616 53 4 as as ADP cana-616 53 5 a a DET cana-616 53 6 building building NOUN cana-616 53 7 block block NOUN cana-616 53 8 for for ADP cana-616 53 9 the the DET cana-616 53 10 methodologies methodology NOUN cana-616 53 11 discussed discuss VERB cana-616 53 12 in in ADP cana-616 53 13 our our PRON cana-616 53 14 study study NOUN cana-616 53 15 , , PUNCT cana-616 53 16 providing provide VERB cana-616 53 17 a a DET cana-616 53 18 deep deep ADJ cana-616 53 19 dive dive NOUN cana-616 53 20 into into ADP cana-616 53 21 the the DET cana-616 53 22 optimization optimization NOUN cana-616 53 23 of of ADP cana-616 53 24 machine machine NOUN cana-616 53 25 learning learn VERB cana-616 53 26 algorithms algorithm NOUN cana-616 53 27 for for ADP cana-616 53 28 challenging challenge VERB cana-616 53 29 datasets dataset NOUN cana-616 53 30 like like ADP cana-616 53 31 image image NOUN cana-616 53 32 classification classification NOUN cana-616 53 33 in in ADP cana-616 53 34 veterinary veterinary ADJ cana-616 53 35 diagnostics diagnostic NOUN cana-616 53 36 . . PUNCT cana-616 54 1 advanced advanced ADJ cana-616 54 2 gaussian gaussian ADJ cana-616 54 3 process process NOUN cana-616 54 4 ( ( PUNCT cana-616 54 5 gp gp NOUN cana-616 54 6 ) ) PUNCT cana-616 54 7 formulations formulation NOUN cana-616 54 8 predictive predictive ADJ cana-616 54 9 distribution distribution NOUN cana-616 54 10 for for ADP cana-616 54 11 gp gp NOUN cana-616 54 12 πœ‡(π‘₯βˆ— πœ‡(π‘₯βˆ— PROPN cana-616 54 13 ) ) PUNCT cana-616 55 1 βˆ’ βˆ’ PROPN cana-616 56 1 π‘˜(π‘₯βˆ— π‘˜(π‘₯βˆ— NOUN cana-616 56 2 , , PUNCT cana-616 56 3 𝑋)(π‘˜(𝑋 𝑋)(π‘˜(𝑋 PROPN cana-616 56 4 , , PUNCT cana-616 56 5 𝑋 𝑋 PROPN cana-616 56 6 ) ) PUNCT cana-616 56 7 + + NUM cana-616 56 8 πœŽπ‘› πœŽπ‘› PRON cana-616 56 9 2𝐼)βˆ’1𝑦 2𝐼)βˆ’1𝑦 NUM cana-616 56 10 ( ( PUNCT cana-616 56 11 11 11 NUM cana-616 56 12 ) ) PUNCT cana-616 56 13 where where SCONJ cana-616 56 14 π‘₯βˆ— π‘₯βˆ— PROPN cana-616 56 15 is be AUX cana-616 56 16 a a DET cana-616 56 17 new new ADJ cana-616 56 18 input input NOUN cana-616 56 19 , , PUNCT cana-616 56 20 𝑋 𝑋 PROPN cana-616 56 21 is be AUX cana-616 56 22 the the DET cana-616 56 23 matrix matrix NOUN cana-616 56 24 of of ADP cana-616 56 25 training training NOUN cana-616 56 26 inputs input NOUN cana-616 56 27 , , PUNCT cana-616 56 28 𝑦 𝑦 NOUN cana-616 56 29 is be AUX cana-616 56 30 the the DET cana-616 56 31 vector vector NOUN cana-616 56 32 of of ADP cana-616 56 33 training training NOUN cana-616 56 34 outputs output NOUN cana-616 56 35 , , PUNCT cana-616 56 36 π‘˜ π‘˜ PRON cana-616 56 37 denotes denote VERB cana-616 56 38 the the DET cana-616 56 39 covariance covariance NOUN cana-616 56 40 matrix matrix NOUN cana-616 56 41 , , PUNCT cana-616 56 42 and and CCONJ cana-616 56 43 πœŽπ‘› πœŽπ‘› DET cana-616 56 44 2 2 NUM cana-616 56 45 is be AUX cana-616 56 46 the the DET cana-616 56 47 noise noise NOUN cana-616 56 48 term term NOUN cana-616 56 49 . . PUNCT cana-616 57 1 covariance covariance NOUN cana-616 57 2 matrix matrix NOUN cana-616 57 3 computation computation NOUN cana-616 57 4 𝐾 𝐾 PROPN cana-616 57 5 βˆ’ βˆ’ PROPN cana-616 58 1 [ [ X cana-616 58 2 π‘˜(π‘₯𝑖 π‘˜(π‘₯𝑖 NUM cana-616 58 3 , , PUNCT cana-616 58 4 π‘₯𝑗)]𝑖,π‘—βˆ’1 π‘₯𝑗)]𝑖,π‘—βˆ’1 PROPN cana-616 58 5 𝑁 𝑁 PROPN cana-616 58 6 ( ( PUNCT cana-616 58 7 12 12 NUM cana-616 58 8 ) ) PUNCT cana-616 58 9 this this PRON cana-616 58 10 is be AUX cana-616 58 11 the the DET cana-616 58 12 covariance covariance NOUN cana-616 58 13 matrix matrix NOUN cana-616 58 14 𝐾 𝐾 PROPN cana-616 58 15 for for ADP cana-616 58 16 inputs input NOUN cana-616 58 17 π‘₯𝑖 π‘₯𝑖 PROPN cana-616 58 18 and and CCONJ cana-616 58 19 π‘₯𝑗 π‘₯𝑗 PROPN cana-616 58 20 in in ADP cana-616 58 21 the the DET cana-616 58 22 dataset dataset NOUN cana-616 58 23 . . PUNCT cana-616 59 1 model model NOUN cana-616 59 2 training training NOUN cana-616 59 3 and and CCONJ cana-616 59 4 optimization optimization NOUN cana-616 59 5 techniques technique NOUN cana-616 59 6 batch batch VERB cana-616 59 7 gradient gradient ADJ cana-616 59 8 descent descent NOUN cana-616 59 9 πœƒ:βˆ’πœƒ πœƒ:βˆ’πœƒ NOUN cana-616 59 10 βˆ’ βˆ’ ADP cana-616 59 11 πœ‚ πœ‚ NOUN cana-616 59 12 β‹… β‹… X cana-616 59 13 βˆ‡πœƒπ½(πœƒ βˆ‡πœƒπ½(πœƒ NUM cana-616 59 14 ) ) PUNCT cana-616 59 15 ( ( PUNCT cana-616 59 16 13 13 NUM cana-616 59 17 ) ) PUNCT cana-616 59 18 where where SCONJ cana-616 59 19 πœ‚ πœ‚ NOUN cana-616 59 20 is be AUX cana-616 59 21 the the DET cana-616 59 22 learning learning NOUN cana-616 59 23 rate rate NOUN cana-616 59 24 and and CCONJ cana-616 59 25 𝐽(πœƒ 𝐽(πœƒ NUM cana-616 59 26 ) ) PUNCT cana-616 59 27 is be AUX cana-616 59 28 the the DET cana-616 59 29 cost cost NOUN cana-616 59 30 function function NOUN cana-616 59 31 . . PUNCT cana-616 60 1 stochastic stochastic ADJ cana-616 60 2 gradient gradient ADJ cana-616 60 3 descent descent NOUN cana-616 60 4 πœƒ:βˆ’πœƒ πœƒ:βˆ’πœƒ NOUN cana-616 60 5 βˆ’ βˆ’ ADP cana-616 60 6 πœ‚ πœ‚ PROPN cana-616 60 7 β‹… β‹… PROPN cana-616 60 8 βˆ‡πœƒπ½(πœƒ βˆ‡πœƒπ½(πœƒ NUM cana-616 60 9 ; ; PUNCT cana-616 60 10 π‘₯ π‘₯ PRON cana-616 60 11 ( ( PUNCT cana-616 60 12 𝑖 𝑖 NOUN cana-616 60 13 ) ) PUNCT cana-616 60 14 , , PUNCT cana-616 60 15 𝑦(𝑖 𝑦(𝑖 NOUN cana-616 60 16 ) ) PUNCT cana-616 60 17 ) ) PUNCT cana-616 61 1 ( ( PUNCT cana-616 61 2 14 14 NUM cana-616 61 3 ) ) PUNCT cana-616 61 4 unlike unlike ADP cana-616 61 5 batch batch NOUN cana-616 61 6 gradient gradient ADJ cana-616 61 7 descent descent NOUN cana-616 61 8 , , PUNCT cana-616 61 9 updates update NOUN cana-616 61 10 are be AUX cana-616 61 11 made make VERB cana-616 61 12 for for ADP cana-616 61 13 each each DET cana-616 61 14 training training NOUN cana-616 61 15 example example NOUN cana-616 61 16 π‘₯(𝑖 π‘₯(𝑖 PROPN cana-616 61 17 ) ) PUNCT cana-616 61 18 , , PUNCT cana-616 61 19 𝑦(𝑖 𝑦(𝑖 NOUN cana-616 61 20 ) ) PUNCT cana-616 61 21 . . PUNCT cana-616 62 1 mini mini ADJ cana-616 62 2 - - NOUN cana-616 62 3 batch batch ADJ cana-616 62 4 gradient gradient ADJ cana-616 62 5 descent descent NOUN cana-616 62 6 πœƒ:βˆ’πœƒ πœƒ:βˆ’πœƒ NOUN cana-616 62 7 βˆ’ βˆ’ ADP cana-616 62 8 πœ‚ πœ‚ PROPN cana-616 62 9 β‹… β‹… PROPN cana-616 62 10 βˆ‡πœƒπ½(πœƒ βˆ‡πœƒπ½(πœƒ NUM cana-616 62 11 ; ; PUNCT cana-616 62 12 𝑋 𝑋 PROPN cana-616 62 13 ( ( PUNCT cana-616 62 14 𝑖:𝑖+𝑛 𝑖:𝑖+𝑛 NOUN cana-616 62 15 ) ) PUNCT cana-616 62 16 , , PUNCT cana-616 62 17 π‘Œ(𝑖:𝑖+𝑛 π‘Œ(𝑖:𝑖+𝑛 PROPN cana-616 62 18 ) ) PUNCT cana-616 62 19 ) ) PUNCT cana-616 62 20 ( ( PUNCT cana-616 62 21 15 15 X cana-616 62 22 ) ) PUNCT cana-616 62 23 this this PRON cana-616 62 24 is be AUX cana-616 62 25 a a DET cana-616 62 26 hybrid hybrid ADJ cana-616 62 27 approach approach NOUN cana-616 62 28 where where SCONJ cana-616 62 29 updates update NOUN cana-616 62 30 are be AUX cana-616 62 31 made make VERB cana-616 62 32 for for ADP cana-616 62 33 mini mini NOUN cana-616 62 34 - - NOUN cana-616 62 35 batches batch NOUN cana-616 62 36 of of ADP cana-616 62 37 𝑛 𝑛 DET cana-616 62 38 training training NOUN cana-616 62 39 examples example NOUN cana-616 62 40 . . PUNCT cana-616 63 1 regularization regularization NOUN cana-616 63 2 techniques technique NOUN cana-616 63 3 l2 l2 NOUN cana-616 63 4 regularization regularization NOUN cana-616 63 5 𝐽(πœƒ 𝐽(πœƒ NOUN cana-616 63 6 ) ) PUNCT cana-616 63 7 βˆ’ βˆ’ NOUN cana-616 63 8 loss⁑(πœƒ loss⁑(πœƒ NOUN cana-616 63 9 ) ) PUNCT cana-616 64 1 + + CCONJ cana-616 64 2 πœ†βˆ‘ πœ†βˆ‘ PUNCT cana-616 64 3 β€Š β€Š SPACE cana-616 64 4 𝑛 𝑛 PRON cana-616 64 5 π‘—βˆ’1 π‘—βˆ’1 PROPN cana-616 64 6 πœƒπ‘— πœƒπ‘— VERB cana-616 64 7 2 2 NUM cana-616 64 8 ( ( PUNCT cana-616 64 9 16 16 NUM cana-616 64 10 ) ) PUNCT cana-616 64 11 this this PRON cana-616 64 12 adds add VERB cana-616 64 13 a a DET cana-616 64 14 penalty penalty NOUN cana-616 64 15 to to ADP cana-616 64 16 the the DET cana-616 64 17 loss loss NOUN cana-616 64 18 function function NOUN cana-616 64 19 to to PART cana-616 64 20 preverit preverit VERB cana-616 64 21 overfitting overfitte VERB cana-616 64 22 by by ADP cana-616 64 23 keeping keep VERB cana-616 64 24 the the DET cana-616 64 25 weights weight NOUN cana-616 64 26 small small ADJ cana-616 64 27 . . PUNCT cana-616 65 1 l1 l1 PROPN cana-616 65 2 regularization regularization PROPN cana-616 65 3 𝐽(πœƒ 𝐽(πœƒ NOUN cana-616 65 4 ) ) PUNCT cana-616 66 1 βˆ’ βˆ’ NOUN cana-616 66 2 loss⁑(πœƒ loss⁑(πœƒ NOUN cana-616 66 3 ) ) PUNCT cana-616 67 1 + + CCONJ cana-616 67 2 πœ†βˆ‘ πœ†βˆ‘ PUNCT cana-616 67 3 β€Š β€Š SPACE cana-616 67 4 𝑛 𝑛 PRON cana-616 67 5 π‘—βˆ’1 π‘—βˆ’1 PROPN cana-616 67 6 |πœƒπ‘—| |πœƒπ‘—| INTJ cana-616 67 7 ( ( PUNCT cana-616 67 8 17 17 NUM cana-616 67 9 ) ) PUNCT cana-616 67 10 l1 l1 PROPN cana-616 67 11 regularization regularization NOUN cana-616 67 12 can can AUX cana-616 67 13 lead lead VERB cana-616 67 14 to to ADP cana-616 67 15 sparse sparse ADJ cana-616 67 16 models model NOUN cana-616 67 17 , , PUNCT cana-616 67 18 where where SCONJ cana-616 67 19 some some DET cana-616 67 20 feature feature NOUN cana-616 67 21 weights weight NOUN cana-616 67 22 are be AUX cana-616 67 23 zero zero NUM cana-616 67 24 . . PUNCT cana-616 68 1 performance performance NOUN cana-616 68 2 evaluation evaluation NOUN cana-616 68 3 metrics metric NOUN cana-616 68 4 communications communication NOUN cana-616 68 5 on on ADP cana-616 68 6 applied apply VERB cana-616 68 7 nonlinear nonlinear ADJ cana-616 68 8 analysis analysis NOUN cana-616 68 9 issn issn NOUN cana-616 68 10 : : PUNCT cana-616 68 11 1074 1074 NUM cana-616 68 12 - - PUNCT cana-616 68 13 133x 133x NUM cana-616 68 14 vol vol NOUN cana-616 68 15 31 31 NUM cana-616 68 16 no no NOUN cana-616 68 17 . . PUNCT cana-616 69 1 2s 2s NUM cana-616 69 2 ( ( PUNCT cana-616 69 3 2024 2024 NUM cana-616 69 4 ) ) PUNCT cana-616 69 5 123 123 NUM cana-616 69 6 https://internationalpubls.com https://internationalpubls.com X cana-616 69 7 precision precision NOUN cana-616 69 8 precision precision NOUN cana-616 69 9 = = SYM cana-616 69 10 𝑇𝑃 𝑇𝑃 NOUN cana-616 70 1 𝑇𝑃′+𝐹𝑃 𝑇𝑃′+𝐹𝑃 NOUN cana-616 70 2 ( ( PUNCT cana-616 70 3 18 18 NUM cana-616 70 4 ) ) PUNCT cana-616 70 5 precision precision NOUN cana-616 70 6 measures measure NOUN cana-616 70 7 the the DET cana-616 70 8 accuracy accuracy NOUN cana-616 70 9 of of ADP cana-616 70 10 positive positive ADJ cana-616 70 11 predictions prediction NOUN cana-616 70 12 . . PUNCT cana-616 71 1 recall recall NOUN cana-616 71 2 ( ( PUNCT cana-616 71 3 sensitivity sensitivity NOUN cana-616 71 4 ) ) PUNCT cana-616 71 5 recall recall NOUN cana-616 71 6 = = SYM cana-616 71 7 𝑇𝑃 𝑇𝑃 PROPN cana-616 71 8 𝑇𝑇𝑃+𝐹𝑁 𝑇𝑇𝑃+𝐹𝑁 PROPN cana-616 71 9 ( ( PUNCT cana-616 71 10 19 19 NUM cana-616 71 11 ) ) PUNCT cana-616 71 12 recall recall NOUN cana-616 71 13 measures measure NOUN cana-616 71 14 the the DET cana-616 71 15 ability ability NOUN cana-616 71 16 of of ADP cana-616 71 17 a a DET cana-616 71 18 model model NOUN cana-616 71 19 to to PART cana-616 71 20 find find VERB cana-616 71 21 all all DET cana-616 71 22 relevant relevant ADJ cana-616 71 23 cases case NOUN cana-616 71 24 ( ( PUNCT cana-616 71 25 positive positive ADJ cana-616 71 26 samples sample NOUN cana-616 71 27 ) ) PUNCT cana-616 71 28 . . PUNCT cana-616 72 1 f1score f1score NOUN cana-616 72 2 𝐹1 𝐹1 PROPN cana-616 72 3 = = SYM cana-616 72 4 2 2 NUM cana-616 72 5 Γ— Γ— NOUN cana-616 72 6 1 1 NUM cana-616 72 7 resecision resecision NOUN cana-616 72 8 Γ— Γ— NOUN cana-616 72 9 recall recall NOUN cana-616 72 10 precision precision PROPN cana-616 72 11 βˆ’ βˆ’ PROPN cana-616 72 12 recaill recaill NOUN cana-616 72 13 the the DET cana-616 72 14 f1 f1 PROPN cana-616 72 15 score score NOUN cana-616 72 16 is be AUX cana-616 72 17 a a DET cana-616 72 18 harmonic harmonic ADJ cana-616 72 19 mean mean NOUN cana-616 72 20 of of ADP cana-616 72 21 precision precision NOUN cana-616 72 22 and and CCONJ cana-616 72 23 recall recall NOUN cana-616 72 24 , , PUNCT cana-616 72 25 useful useful ADJ cana-616 72 26 for for ADP cana-616 72 27 unbalanced unbalanced ADJ cana-616 72 28 classes class NOUN cana-616 72 29 . . PUNCT cana-616 73 1 advanced advanced ADJ cana-616 73 2 optimization optimization NOUN cana-616 73 3 techniques technique NOUN cana-616 73 4 momentum momentum NOUN cana-616 73 5 - - PUNCT cana-616 73 6 based base VERB cana-616 73 7 update update NOUN cana-616 73 8 𝑣𝑑 𝑣𝑑 ADP cana-616 73 9 βˆ’ βˆ’ PROPN cana-616 73 10 π›Ύπ‘£π‘‘βˆ’1 π›Ύπ‘£π‘‘βˆ’1 PROPN cana-616 73 11 + + NUM cana-616 73 12 πœ‚βˆ‡πœƒπ½(πœƒ πœ‚βˆ‡πœƒπ½(πœƒ NOUN cana-616 73 13 ) ) PUNCT cana-616 73 14 πœƒ:βˆ’πœƒ πœƒ:βˆ’πœƒ NOUN cana-616 73 15 βˆ’ βˆ’ PROPN cana-616 73 16 𝑣𝑑 𝑣𝑑 ADP cana-616 73 17 ( ( PUNCT cana-616 73 18 20 20 NUM cana-616 73 19 ) ) PUNCT cana-616 73 20 where where SCONJ cana-616 73 21 𝛾 𝛾 NOUN cana-616 73 22 is be AUX cana-616 73 23 the the DET cana-616 73 24 momentum momentum NOUN cana-616 73 25 coefficient coefficient NOUN cana-616 73 26 . . PUNCT cana-616 74 1 advanced advanced ADJ cana-616 74 2 optimization optimization NOUN cana-616 74 3 techniques technique NOUN cana-616 74 4 momentum momentum NOUN cana-616 74 5 - - PUNCT cana-616 74 6 based base VERB cana-616 74 7 update update NOUN cana-616 74 8 𝑣𝑑 𝑣𝑑 ADP cana-616 74 9 βˆ’ βˆ’ PROPN cana-616 74 10 π›Ύπ‘£π‘‘βˆ’1 π›Ύπ‘£π‘‘βˆ’1 PROPN cana-616 74 11 + + NUM cana-616 74 12 πœ‚βˆ‡πœƒπ½(πœƒ πœ‚βˆ‡πœƒπ½(πœƒ NOUN cana-616 74 13 ) ) PUNCT cana-616 74 14 πœƒ:βˆ’πœƒ πœƒ:βˆ’πœƒ NOUN cana-616 74 15 βˆ’ βˆ’ PROPN cana-616 74 16 𝑣𝑑 𝑣𝑑 ADP cana-616 74 17 ( ( PUNCT cana-616 74 18 21 21 NUM cana-616 74 19 ) ) PUNCT cana-616 74 20 where where SCONJ cana-616 74 21 𝛾 𝛾 NOUN cana-616 74 22 is be AUX cana-616 74 23 the the DET cana-616 74 24 momentum momentum NOUN cana-616 74 25 coefficient coefficient NOUN cana-616 74 26 . . PUNCT cana-616 75 1 adam adam PROPN cana-616 75 2 optimization optimization NOUN cana-616 75 3 π‘šπ‘‘ π‘šπ‘‘ PROPN cana-616 75 4 = = PUNCT cana-616 75 5 𝛽1π‘šπ‘‘βˆ’1 𝛽1π‘šπ‘‘βˆ’1 PROPN cana-616 75 6 + + CCONJ cana-616 75 7 ( ( PUNCT cana-616 75 8 1 1 NUM cana-616 75 9 βˆ’ βˆ’ PROPN cana-616 75 10 𝛽1)βˆ‡πœƒπ½(πœƒ 𝛽1)βˆ‡πœƒπ½(πœƒ PROPN cana-616 75 11 ) ) PUNCT cana-616 75 12 𝑣𝑑 𝑣𝑑 ADP cana-616 75 13 = = PUNCT cana-616 75 14 𝛽2π‘£π‘‘βˆ’1 𝛽2π‘£π‘‘βˆ’1 PROPN cana-616 75 15 + + CCONJ cana-616 75 16 ( ( PUNCT cana-616 75 17 1 1 NUM cana-616 75 18 βˆ’ βˆ’ NOUN cana-616 75 19 𝛽2)(βˆ‡πœƒπ½(πœƒ 𝛽2)(βˆ‡πœƒπ½(πœƒ NOUN cana-616 75 20 ) ) PUNCT cana-616 75 21 ) ) PUNCT cana-616 75 22 2 2 NUM cana-616 75 23 οΏ½ οΏ½ PROPN cana-616 75 24 Μ‚ Μ‚ NOUN cana-616 75 25 οΏ½ οΏ½ NOUN cana-616 75 26 𝑑 𝑑 NOUN cana-616 75 27 = = SYM cana-616 75 28 π‘šπ‘‘ π‘šπ‘‘ PROPN cana-616 75 29 1βˆ’π›½1 1βˆ’π›½1 NUM cana-616 75 30 𝐻 𝐻 PROPN cana-616 75 31 οΏ½ οΏ½ PROPN cana-616 75 32 Μ‚ Μ‚ NOUN cana-616 75 33 οΏ½ οΏ½ NOUN cana-616 75 34 𝑑 𝑑 NOUN cana-616 75 35 = = NOUN cana-616 75 36 1 1 NUM cana-616 75 37 1βˆ’π›½2 1βˆ’π›½2 NUM cana-616 75 38 𝑑 𝑑 NOUN cana-616 75 39 πœƒ:= πœƒ:= ADP cana-616 75 40 πœƒ πœƒ NOUN cana-616 75 41 βˆ’ βˆ’ PROPN cana-616 75 42 πœ‹ πœ‹ NOUN cana-616 75 43 οΏ½ οΏ½ PROPN cana-616 75 44 Μƒ Μƒ NOUN cana-616 75 45 οΏ½ οΏ½ NOUN cana-616 75 46 𝑑 𝑑 PART cana-616 75 47 βˆšπ‘£π‘‘+πœ€ βˆšπ‘£π‘‘+πœ€ PROPN cana-616 75 48 ( ( PUNCT cana-616 75 49 22 22 NUM cana-616 75 50 ) ) PUNCT cana-616 75 51 adam adam PROPN cana-616 75 52 combines combine VERB cana-616 75 53 the the DET cana-616 75 54 advantages advantage NOUN cana-616 75 55 of of ADP cana-616 75 56 the the DET cana-616 75 57 adaptive adaptive ADJ cana-616 75 58 gradient gradient ADJ cana-616 75 59 algorithm algorithm NOUN cana-616 75 60 and and CCONJ cana-616 75 61 rmsprop rmsprop NOUN cana-616 75 62 , , PUNCT cana-616 75 63 making make VERB cana-616 75 64 it it PRON cana-616 75 65 generally generally ADV cana-616 75 66 well well ADV cana-616 75 67 - - PUNCT cana-616 75 68 suited suit VERB cana-616 75 69 for for ADP cana-616 75 70 handling handle VERB cana-616 75 71 sparse sparse ADJ cana-616 75 72 gradients gradient NOUN cana-616 75 73 in in ADP cana-616 75 74 noisy noisy ADJ cana-616 75 75 problems problem NOUN cana-616 75 76 . . PUNCT cana-616 76 1 these these DET cana-616 76 2 equations equation NOUN cana-616 76 3 provide provide VERB cana-616 76 4 a a DET cana-616 76 5 mathematical mathematical ADJ cana-616 76 6 backbone backbone NOUN cana-616 76 7 for for ADP cana-616 76 8 understanding understanding NOUN cana-616 76 9 and and CCONJ cana-616 76 10 implementing implement VERB cana-616 76 11 the the DET cana-616 76 12 machine machine NOUN cana-616 76 13 learning learn VERB cana-616 76 14 techniques technique NOUN cana-616 76 15 that that PRON cana-616 76 16 enhance enhance VERB cana-616 76 17 the the DET cana-616 76 18 performance performance NOUN cana-616 76 19 and and CCONJ cana-616 76 20 accuracy accuracy NOUN cana-616 76 21 of of ADP cana-616 76 22 complex complex ADJ cana-616 76 23 models model NOUN cana-616 76 24 such such ADJ cana-616 76 25 as as ADP cana-616 76 26 the the DET cana-616 76 27 random random ADJ cana-616 76 28 forest forest NOUN cana-616 76 29 classifier classifier NOUN cana-616 76 30 optimized optimize VERB cana-616 76 31 with with ADP cana-616 76 32 bayesian bayesian NOUN cana-616 76 33 approaches approach NOUN cana-616 76 34 . . PUNCT cana-616 77 1 these these DET cana-616 77 2 foundational foundational ADJ cana-616 77 3 concepts concept NOUN cana-616 77 4 are be AUX cana-616 77 5 essential essential ADJ cana-616 77 6 for for ADP cana-616 77 7 optimizing optimize VERB cana-616 77 8 and and CCONJ cana-616 77 9 evaluating evaluate VERB cana-616 77 10 the the DET cana-616 77 11 performance performance NOUN cana-616 77 12 of of ADP cana-616 77 13 models model NOUN cana-616 77 14 in in ADP cana-616 77 15 real real ADJ cana-616 77 16 - - PUNCT cana-616 77 17 world world NOUN cana-616 77 18 applications application NOUN cana-616 77 19 , , PUNCT cana-616 77 20 particularly particularly ADV cana-616 77 21 in in ADP cana-616 77 22 challenging challenging ADJ cana-616 77 23 domains domain NOUN cana-616 77 24 like like ADP cana-616 77 25 image image NOUN cana-616 77 26 classification classification NOUN cana-616 77 27 for for ADP cana-616 77 28 diagnosing diagnose VERB cana-616 77 29 diseases disease NOUN cana-616 77 30 . . PUNCT cana-616 78 1 communications communication NOUN cana-616 78 2 on on ADP cana-616 78 3 applied apply VERB cana-616 78 4 nonlinear nonlinear ADJ cana-616 78 5 analysis analysis NOUN cana-616 78 6 issn issn NOUN cana-616 78 7 : : PUNCT cana-616 78 8 1074 1074 NUM cana-616 78 9 - - PUNCT cana-616 78 10 133x 133x NUM cana-616 78 11 vol vol NOUN cana-616 78 12 31 31 NUM cana-616 78 13 no no NOUN cana-616 78 14 . . PUNCT cana-616 79 1 2s 2s NUM cana-616 79 2 ( ( PUNCT cana-616 79 3 2024 2024 NUM cana-616 79 4 ) ) PUNCT cana-616 79 5 124 124 NUM cana-616 79 6 https://internationalpubls.com https://internationalpubls.com X cana-616 79 7 2 2 X cana-616 79 8 . . X cana-616 79 9 literature literature NOUN cana-616 79 10 review review PROPN cana-616 79 11 bayesian bayesian NOUN cana-616 79 12 optimization optimization NOUN cana-616 79 13 has have AUX cana-616 79 14 emerged emerge VERB cana-616 79 15 as as ADP cana-616 79 16 a a DET cana-616 79 17 promising promising ADJ cana-616 79 18 methodology methodology NOUN cana-616 79 19 for for ADP cana-616 79 20 optimizing optimize VERB cana-616 79 21 complex complex ADJ cana-616 79 22 functions function NOUN cana-616 79 23 , , PUNCT cana-616 79 24 particularly particularly ADV cana-616 79 25 in in ADP cana-616 79 26 the the DET cana-616 79 27 context context NOUN cana-616 79 28 of of ADP cana-616 79 29 tuning tune VERB cana-616 79 30 hyperparameters hyperparameter NOUN cana-616 79 31 for for ADP cana-616 79 32 machine machine NOUN cana-616 79 33 learning learning NOUN cana-616 79 34 algorithms algorithm NOUN cana-616 79 35 . . PUNCT cana-616 80 1 by by ADP cana-616 80 2 iteratively iteratively ADV cana-616 80 3 selecting select VERB cana-616 80 4 parameter parameter NOUN cana-616 80 5 configurations configuration NOUN cana-616 80 6 based base VERB cana-616 80 7 on on ADP cana-616 80 8 past past ADJ cana-616 80 9 observations observation NOUN cana-616 80 10 and and CCONJ cana-616 80 11 probabilistic probabilistic ADJ cana-616 80 12 models model NOUN cana-616 80 13 , , PUNCT cana-616 80 14 bayesian bayesian NOUN cana-616 80 15 optimization optimization NOUN cana-616 80 16 efficiently efficiently ADV cana-616 80 17 explores explore VERB cana-616 80 18 the the DET cana-616 80 19 parameter parameter NOUN cana-616 80 20 space space NOUN cana-616 80 21 , , PUNCT cana-616 80 22 leading lead VERB cana-616 80 23 to to ADP cana-616 80 24 improved improved ADJ cana-616 80 25 model model NOUN cana-616 80 26 performance performance NOUN cana-616 80 27 . . PUNCT cana-616 81 1 random random ADJ cana-616 81 2 forest forest NOUN cana-616 81 3 classifiers classifier NOUN cana-616 81 4 have have AUX cana-616 81 5 gained gain VERB cana-616 81 6 popularity popularity NOUN cana-616 81 7 in in ADP cana-616 81 8 machine machine NOUN cana-616 81 9 learning learning NOUN cana-616 81 10 due due ADP cana-616 81 11 to to ADP cana-616 81 12 their their PRON cana-616 81 13 ability ability NOUN cana-616 81 14 to to PART cana-616 81 15 handle handle VERB cana-616 81 16 nonlinear nonlinear ADJ cana-616 81 17 relationships relationship NOUN cana-616 81 18 in in ADP cana-616 81 19 data datum NOUN cana-616 81 20 and and CCONJ cana-616 81 21 their their PRON cana-616 81 22 robustness robustness NOUN cana-616 81 23 against against ADP cana-616 81 24 overfitting overfitte VERB cana-616 81 25 . . PUNCT cana-616 82 1 however however ADV cana-616 82 2 , , PUNCT cana-616 82 3 the the DET cana-616 82 4 performance performance NOUN cana-616 82 5 of of ADP cana-616 82 6 random random ADJ cana-616 82 7 forest forest NOUN cana-616 82 8 models model NOUN cana-616 82 9 heavily heavily ADV cana-616 82 10 relies rely VERB cana-616 82 11 on on ADP cana-616 82 12 the the DET cana-616 82 13 selection selection NOUN cana-616 82 14 of of ADP cana-616 82 15 hyperparameters hyperparameter NOUN cana-616 82 16 , , PUNCT cana-616 82 17 which which PRON cana-616 82 18 can can AUX cana-616 82 19 be be AUX cana-616 82 20 a a DET cana-616 82 21 challenging challenging ADJ cana-616 82 22 and and CCONJ cana-616 82 23 time time NOUN cana-616 82 24 - - PUNCT cana-616 82 25 consuming consume VERB cana-616 82 26 task task NOUN cana-616 82 27 , , PUNCT cana-616 82 28 especially especially ADV cana-616 82 29 for for ADP cana-616 82 30 datasets dataset NOUN cana-616 82 31 with with ADP cana-616 82 32 complex complex ADJ cana-616 82 33 structures structure NOUN cana-616 82 34 [ [ X cana-616 82 35 7 7 NUM cana-616 82 36 - - SYM cana-616 82 37 15 15 NUM cana-616 82 38 ] ] PUNCT cana-616 82 39 . . PUNCT cana-616 83 1 to to PART cana-616 83 2 address address VERB cana-616 83 3 this this DET cana-616 83 4 challenge challenge NOUN cana-616 83 5 , , PUNCT cana-616 83 6 researchers researcher NOUN cana-616 83 7 have have AUX cana-616 83 8 proposed propose VERB cana-616 83 9 integrating integrate VERB cana-616 83 10 bayesian bayesian NOUN cana-616 83 11 optimization optimization NOUN cana-616 83 12 with with ADP cana-616 83 13 random random ADJ cana-616 83 14 forest forest NOUN cana-616 83 15 classifiers classifier NOUN cana-616 83 16 to to PART cana-616 83 17 automate automate VERB cana-616 83 18 the the DET cana-616 83 19 hyperparameter hyperparameter NOUN cana-616 83 20 tuning tuning NOUN cana-616 83 21 process process NOUN cana-616 83 22 . . PUNCT cana-616 84 1 by by ADP cana-616 84 2 leveraging leverage VERB cana-616 84 3 bayesian bayesian NOUN cana-616 84 4 optimization optimization NOUN cana-616 84 5 's 's PART cana-616 84 6 ability ability NOUN cana-616 84 7 to to PART cana-616 84 8 consider consider VERB cana-616 84 9 uncertainty uncertainty NOUN cana-616 84 10 and and CCONJ cana-616 84 11 intelligently intelligently ADV cana-616 84 12 explore explore VERB cana-616 84 13 the the DET cana-616 84 14 hyperparameter hyperparameter NOUN cana-616 84 15 space space NOUN cana-616 84 16 , , PUNCT cana-616 84 17 these these DET cana-616 84 18 hybrid hybrid ADJ cana-616 84 19 approaches approach NOUN cana-616 84 20 aim aim VERB cana-616 84 21 to to PART cana-616 84 22 enhance enhance VERB cana-616 84 23 the the DET cana-616 84 24 performance performance NOUN cana-616 84 25 and and CCONJ cana-616 84 26 efficiency efficiency NOUN cana-616 84 27 of of ADP cana-616 84 28 random random ADJ cana-616 84 29 forest forest NOUN cana-616 84 30 models model NOUN cana-616 84 31 . . PUNCT cana-616 85 1 recent recent ADJ cana-616 85 2 advancements advancement NOUN cana-616 85 3 in in ADP cana-616 85 4 bayesian bayesian NOUN cana-616 85 5 optimization optimization NOUN cana-616 85 6 have have AUX cana-616 85 7 focused focus VERB cana-616 85 8 on on ADP cana-616 85 9 incorporating incorporate VERB cana-616 85 10 gradient gradient NOUN cana-616 85 11 and and CCONJ cana-616 85 12 hessian hessian ADJ cana-616 85 13 computations computation NOUN cana-616 85 14 into into ADP cana-616 85 15 the the DET cana-616 85 16 optimization optimization NOUN cana-616 85 17 process process NOUN cana-616 85 18 . . PUNCT cana-616 86 1 by by ADP cana-616 86 2 utilizing utilize VERB cana-616 86 3 information information NOUN cana-616 86 4 about about ADP cana-616 86 5 the the DET cana-616 86 6 first first ADJ cana-616 86 7 and and CCONJ cana-616 86 8 second second ADJ cana-616 86 9 derivatives derivative NOUN cana-616 86 10 of of ADP cana-616 86 11 the the DET cana-616 86 12 objective objective ADJ cana-616 86 13 function function NOUN cana-616 86 14 , , PUNCT cana-616 86 15 these these DET cana-616 86 16 approaches approach NOUN cana-616 86 17 guide guide VERB cana-616 86 18 the the DET cana-616 86 19 optimization optimization NOUN cana-616 86 20 process process NOUN cana-616 86 21 more more ADV cana-616 86 22 effectively effectively ADV cana-616 86 23 , , PUNCT cana-616 86 24 leading lead VERB cana-616 86 25 to to ADP cana-616 86 26 faster fast ADJ cana-616 86 27 convergence convergence NOUN cana-616 86 28 and and CCONJ cana-616 86 29 potentially potentially ADV cana-616 86 30 better well ADJ cana-616 86 31 solutions solution NOUN cana-616 86 32 . . PUNCT cana-616 87 1 however however ADV cana-616 87 2 , , PUNCT cana-616 87 3 while while SCONJ cana-616 87 4 bayesian bayesian NOUN cana-616 87 5 optimization optimization NOUN cana-616 87 6 with with ADP cana-616 87 7 gradient gradient NOUN cana-616 87 8 and and CCONJ cana-616 87 9 hessian hessian ADJ cana-616 87 10 computation computation NOUN cana-616 87 11 has have AUX cana-616 87 12 shown show VERB cana-616 87 13 promising promising ADJ cana-616 87 14 results result NOUN cana-616 87 15 in in ADP cana-616 87 16 various various ADJ cana-616 87 17 optimization optimization NOUN cana-616 87 18 tasks task NOUN cana-616 87 19 , , PUNCT cana-616 87 20 its its PRON cana-616 87 21 application application NOUN cana-616 87 22 to to ADP cana-616 87 23 improving improve VERB cana-616 87 24 random random ADJ cana-616 87 25 forest forest NOUN cana-616 87 26 classifiers classifier NOUN cana-616 87 27 for for ADP cana-616 87 28 non non ADJ cana-616 87 29 - - ADJ cana-616 87 30 linear linear ADJ cana-616 87 31 classification classification NOUN cana-616 87 32 problems problem NOUN cana-616 87 33 remains remain VERB cana-616 87 34 relatively relatively ADV cana-616 87 35 unexplored unexplored ADJ cana-616 87 36 [ [ PUNCT cana-616 87 37 12 12 NUM cana-616 87 38 - - SYM cana-616 87 39 25 25 NUM cana-616 87 40 ] ] PUNCT cana-616 87 41 . . PUNCT cana-616 88 1 in in ADP cana-616 88 2 this this DET cana-616 88 3 context context NOUN cana-616 88 4 , , PUNCT cana-616 88 5 this this DET cana-616 88 6 study study NOUN cana-616 88 7 aims aim VERB cana-616 88 8 to to PART cana-616 88 9 statistically statistically ADV cana-616 88 10 assess assess VERB cana-616 88 11 the the DET cana-616 88 12 effectiveness effectiveness NOUN cana-616 88 13 of of ADP cana-616 88 14 a a DET cana-616 88 15 novel novel ADJ cana-616 88 16 bayesian bayesian NOUN cana-616 88 17 optimization optimization NOUN cana-616 88 18 gradient gradient NOUN cana-616 88 19 and and CCONJ cana-616 88 20 hessian hessian ADJ cana-616 88 21 computation computation NOUN cana-616 88 22 - - PUNCT cana-616 88 23 based base VERB cana-616 88 24 approach approach NOUN cana-616 88 25 for for ADP cana-616 88 26 improving improve VERB cana-616 88 27 random random ADJ cana-616 88 28 forest forest NOUN cana-616 88 29 classifiers classifier NOUN cana-616 88 30 on on ADP cana-616 88 31 nonlinear nonlinear ADJ cana-616 88 32 classification classification NOUN cana-616 88 33 problems problem NOUN cana-616 88 34 . . PUNCT cana-616 89 1 by by ADP cana-616 89 2 evaluating evaluate VERB cana-616 89 3 the the DET cana-616 89 4 performance performance NOUN cana-616 89 5 of of ADP cana-616 89 6 the the DET cana-616 89 7 proposed propose VERB cana-616 89 8 approach approach NOUN cana-616 89 9 on on ADP cana-616 89 10 a a DET cana-616 89 11 dataset dataset NOUN cana-616 89 12 of of ADP cana-616 89 13 annotated annotate VERB cana-616 89 14 images image NOUN cana-616 89 15 depicting depict VERB cana-616 89 16 stages stage NOUN cana-616 89 17 of of ADP cana-616 89 18 lumpy lumpy ADJ cana-616 89 19 skin skin NOUN cana-616 89 20 disease disease NOUN cana-616 89 21 and and CCONJ cana-616 89 22 comparing compare VERB cana-616 89 23 it it PRON cana-616 89 24 with with ADP cana-616 89 25 conventional conventional ADJ cana-616 89 26 methods method NOUN cana-616 89 27 , , PUNCT cana-616 89 28 this this DET cana-616 89 29 study study NOUN cana-616 89 30 contributes contribute VERB cana-616 89 31 to to ADP cana-616 89 32 the the DET cana-616 89 33 advancement advancement NOUN cana-616 89 34 of of ADP cana-616 89 35 machine machine NOUN cana-616 89 36 learning learn VERB cana-616 89 37 algorithms algorithm NOUN cana-616 89 38 for for ADP cana-616 89 39 image image NOUN cana-616 89 40 classification classification NOUN cana-616 89 41 tasks task NOUN cana-616 89 42 . . PUNCT cana-616 90 1 moreover moreover ADV cana-616 90 2 , , PUNCT cana-616 90 3 the the DET cana-616 90 4 findings finding NOUN cana-616 90 5 of of ADP cana-616 90 6 this this DET cana-616 90 7 study study NOUN cana-616 90 8 suggest suggest VERB cana-616 90 9 the the DET cana-616 90 10 potential potential NOUN cana-616 90 11 of of ADP cana-616 90 12 the the DET cana-616 90 13 improved improve VERB cana-616 90 14 random random ADJ cana-616 90 15 forest forest NOUN cana-616 90 16 classifier classifier NOUN cana-616 90 17 as as ADP cana-616 90 18 a a DET cana-616 90 19 valuable valuable ADJ cana-616 90 20 tool tool NOUN cana-616 90 21 for for ADP cana-616 90 22 veterinary veterinary ADJ cana-616 90 23 diagnostics diagnostic NOUN cana-616 90 24 and and CCONJ cana-616 90 25 its its PRON cana-616 90 26 adaptability adaptability NOUN cana-616 90 27 for for ADP cana-616 90 28 other other ADJ cana-616 90 29 complex complex ADJ cana-616 90 30 image image NOUN cana-616 90 31 classification classification NOUN cana-616 90 32 tasks task NOUN cana-616 90 33 . . PUNCT cana-616 91 1 3 3 X cana-616 91 2 . . NUM cana-616 91 3 proposed propose VERB cana-616 91 4 solution solution NOUN cana-616 91 5 the the DET cana-616 91 6 skin skin NOUN cana-616 91 7 is be AUX cana-616 91 8 among among ADP cana-616 91 9 the the DET cana-616 91 10 widely widely ADV cana-616 91 11 significant significant ADJ cana-616 91 12 practice practice NOUN cana-616 91 13 areas area NOUN cana-616 91 14 in in ADP cana-616 91 15 veterinary veterinary ADJ cana-616 91 16 medicine medicine NOUN cana-616 91 17 since since SCONJ cana-616 91 18 it it PRON cana-616 91 19 embraces embrace VERB cana-616 91 20 conditions condition NOUN cana-616 91 21 such such ADJ cana-616 91 22 as as ADP cana-616 91 23 skin skin NOUN cana-616 91 24 diseases disease NOUN cana-616 91 25 , , PUNCT cana-616 91 26 nails nail NOUN cana-616 91 27 problems problem NOUN cana-616 91 28 , , PUNCT cana-616 91 29 and and CCONJ cana-616 91 30 hair hair NOUN cana-616 91 31 growth growth NOUN cana-616 91 32 problems problem NOUN cana-616 91 33 . . PUNCT cana-616 92 1 under under ADP cana-616 92 2 this this DET cana-616 92 3 sphere sphere NOUN cana-616 92 4 , , PUNCT cana-616 92 5 lots lot NOUN cana-616 92 6 of of ADP cana-616 92 7 research research NOUN cana-616 92 8 have have AUX cana-616 92 9 been be AUX cana-616 92 10 done do VERB cana-616 92 11 with with ADP cana-616 92 12 respect respect NOUN cana-616 92 13 the the DET cana-616 92 14 secured secure VERB cana-616 92 15 skin skin NOUN cana-616 92 16 - - PUNCT cana-616 92 17 related relate VERB cana-616 92 18 conditions condition NOUN cana-616 92 19 by by ADP cana-616 92 20 using use VERB cana-616 92 21 imaging imaging NOUN cana-616 92 22 and and CCONJ cana-616 92 23 predictive predictive ADJ cana-616 92 24 technologies technology NOUN cana-616 92 25 . . PUNCT cana-616 93 1 in in ADP cana-616 93 2 regard regard NOUN cana-616 93 3 to to AUX cana-616 93 4 lumpy lumpy VERB cana-616 93 5 skin skin NOUN cana-616 93 6 disease disease NOUN cana-616 93 7 , , PUNCT cana-616 93 8 the the DET cana-616 93 9 importance importance NOUN cana-616 93 10 of of ADP cana-616 93 11 early early ADJ cana-616 93 12 detection detection NOUN cana-616 93 13 is be AUX cana-616 93 14 undoubted undoubted ADJ cana-616 93 15 . . PUNCT cana-616 94 1 therefore therefore ADV cana-616 94 2 , , PUNCT cana-616 94 3 there there PRON cana-616 94 4 is be VERB cana-616 94 5 a a DET cana-616 94 6 timely timely ADJ cana-616 94 7 need need NOUN cana-616 94 8 of of ADP cana-616 94 9 innovative innovative ADJ cana-616 94 10 approaches approach NOUN cana-616 94 11 to to PART cana-616 94 12 be be AUX cana-616 94 13 developed develop VERB cana-616 94 14 in in ADP cana-616 94 15 order order NOUN cana-616 94 16 to to PART cana-616 94 17 facilitate facilitate VERB cana-616 94 18 a a DET cana-616 94 19 prompt prompt ADJ cana-616 94 20 identification identification NOUN cana-616 94 21 and and CCONJ cana-616 94 22 verification verification NOUN cana-616 94 23 of of ADP cana-616 94 24 this this DET cana-616 94 25 condition condition NOUN cana-616 94 26 right right ADV cana-616 94 27 from from ADP cana-616 94 28 the the DET cana-616 94 29 beginning beginning NOUN cana-616 94 30 . . PUNCT cana-616 95 1 intensity intensity NOUN cana-616 95 2 based base VERB cana-616 95 3 recognition recognition NOUN cana-616 95 4 of of ADP cana-616 95 5 lsd lsd NOUN cana-616 95 6 by by ADP cana-616 95 7 image image NOUN cana-616 95 8 processing processing NOUN cana-616 95 9 turns turn VERB cana-616 95 10 out out ADP cana-616 95 11 to to PART cana-616 95 12 be be AUX cana-616 95 13 one one NUM cana-616 95 14 of of ADP cana-616 95 15 the the DET cana-616 95 16 effective effective ADJ cana-616 95 17 methods method NOUN cana-616 95 18 that that PRON cana-616 95 19 can can AUX cana-616 95 20 be be AUX cana-616 95 21 used use VERB cana-616 95 22 primarily primarily ADV cana-616 95 23 in in ADP cana-616 95 24 the the DET cana-616 95 25 early early ADJ cana-616 95 26 stage stage NOUN cana-616 95 27 of of ADP cana-616 95 28 the the DET cana-616 95 29 disease disease NOUN cana-616 95 30 particularly particularly ADV cana-616 95 31 in in ADP cana-616 95 32 livestock livestock NOUN cana-616 95 33 to to PART cana-616 95 34 cut cut VERB cana-616 95 35 down down ADP cana-616 95 36 on on ADP cana-616 95 37 the the DET cana-616 95 38 mortality mortality NOUN cana-616 95 39 rate rate NOUN cana-616 95 40 due due ADP cana-616 95 41 to to ADP cana-616 95 42 the the DET cana-616 95 43 skin skin NOUN cana-616 95 44 disease disease NOUN cana-616 95 45 . . PUNCT cana-616 96 1 as as ADP cana-616 96 2 a a DET cana-616 96 3 result result NOUN cana-616 96 4 of of ADP cana-616 96 5 a a DET cana-616 96 6 combination combination NOUN cana-616 96 7 of of ADP cana-616 96 8 existing exist VERB cana-616 96 9 image image NOUN cana-616 96 10 processing processing NOUN cana-616 96 11 technology technology NOUN cana-616 96 12 , , PUNCT cana-616 96 13 the the DET cana-616 96 14 overall overall ADJ cana-616 96 15 aim aim NOUN cana-616 96 16 of of ADP cana-616 96 17 this this DET cana-616 96 18 research research NOUN cana-616 96 19 is be AUX cana-616 96 20 to to PART cana-616 96 21 create create VERB cana-616 96 22 an an DET cana-616 96 23 automatic automatic ADJ cana-616 96 24 tool tool NOUN cana-616 96 25 for for ADP cana-616 96 26 the the DET cana-616 96 27 lsd lsd NOUN cana-616 96 28 diagnosis diagnosis NOUN cana-616 96 29 , , PUNCT cana-616 96 30 particularly particularly ADV cana-616 96 31 a a DET cana-616 96 32 skin skin NOUN cana-616 96 33 disease disease NOUN cana-616 96 34 which which PRON cana-616 96 35 affects affect VERB cana-616 96 36 animals animal NOUN cana-616 96 37 . . PUNCT cana-616 97 1 communications communication NOUN cana-616 97 2 on on ADP cana-616 97 3 applied apply VERB cana-616 97 4 nonlinear nonlinear ADJ cana-616 97 5 analysis analysis NOUN cana-616 97 6 issn issn NOUN cana-616 97 7 : : PUNCT cana-616 97 8 1074 1074 NUM cana-616 97 9 - - PUNCT cana-616 97 10 133x 133x NUM cana-616 97 11 vol vol NOUN cana-616 97 12 31 31 NUM cana-616 97 13 no no NOUN cana-616 97 14 . . PUNCT cana-616 98 1 2s 2s NUM cana-616 98 2 ( ( PUNCT cana-616 98 3 2024 2024 NUM cana-616 98 4 ) ) PUNCT cana-616 98 5 125 125 NUM cana-616 98 6 https://internationalpubls.com https://internationalpubls.com X cana-616 98 7 consequently consequently ADV cana-616 98 8 , , PUNCT cana-616 98 9 our our PRON cana-616 98 10 aim aim NOUN cana-616 98 11 is be AUX cana-616 98 12 to to PART cana-616 98 13 get get VERB cana-616 98 14 this this DET cana-616 98 15 vision vision NOUN cana-616 98 16 accomplished accomplish VERB cana-616 98 17 by by ADP cana-616 98 18 means mean NOUN cana-616 98 19 of of ADP cana-616 98 20 creating create VERB cana-616 98 21 an an DET cana-616 98 22 iot iot NOUN cana-616 98 23 - - PUNCT cana-616 98 24 based base VERB cana-616 98 25 model model NOUN cana-616 98 26 that that PRON cana-616 98 27 employs employ VERB cana-616 98 28 image image NOUN cana-616 98 29 processing processing NOUN cana-616 98 30 methods method NOUN cana-616 98 31 , , PUNCT cana-616 98 32 deep deep ADJ cana-616 98 33 learning learning NOUN cana-616 98 34 algorithms algorithm NOUN cana-616 98 35 , , PUNCT cana-616 98 36 and and CCONJ cana-616 98 37 sensor sensor NOUN cana-616 98 38 technology technology NOUN cana-616 98 39 . . PUNCT cana-616 99 1 by by ADP cana-616 99 2 using use VERB cana-616 99 3 health health NOUN cana-616 99 4 sensors sensor NOUN cana-616 99 5 that that PRON cana-616 99 6 will will AUX cana-616 99 7 be be AUX cana-616 99 8 installed instal VERB cana-616 99 9 in in ADP cana-616 99 10 cattle cattle NOUN cana-616 99 11 , , PUNCT cana-616 99 12 the the DET cana-616 99 13 vitals vital NOUN cana-616 99 14 of of ADP cana-616 99 15 the the DET cana-616 99 16 animals animal NOUN cana-616 99 17 will will AUX cana-616 99 18 be be AUX cana-616 99 19 track track NOUN cana-616 99 20 in in ADP cana-616 99 21 real real ADJ cana-616 99 22 time time NOUN cana-616 99 23 including include VERB cana-616 99 24 analysis analysis NOUN cana-616 99 25 of of ADP cana-616 99 26 data datum NOUN cana-616 99 27 collected collect VERB cana-616 99 28 . . PUNCT cana-616 100 1 the the DET cana-616 100 2 grooming grooming NOUN cana-616 100 3 of of ADP cana-616 100 4 the the DET cana-616 100 5 lsd lsd NOUN cana-616 100 6 image image NOUN cana-616 100 7 datasets dataset NOUN cana-616 100 8 involves involve VERB cana-616 100 9 meticulous meticulous ADJ cana-616 100 10 training training NOUN cana-616 100 11 and and CCONJ cana-616 100 12 testing testing NOUN cana-616 100 13 processes process NOUN cana-616 100 14 , , PUNCT cana-616 100 15 more more ADV cana-616 100 16 importantly importantly ADV cana-616 100 17 , , PUNCT cana-616 100 18 accompanied accompany VERB cana-616 100 19 by by ADP cana-616 100 20 finding find VERB cana-616 100 21 the the DET cana-616 100 22 right right ADJ cana-616 100 23 segmentation segmentation NOUN cana-616 100 24 method method NOUN cana-616 100 25 , , PUNCT cana-616 100 26 resulting result VERB cana-616 100 27 in in ADP cana-616 100 28 pretty pretty ADV cana-616 100 29 good good ADJ cana-616 100 30 detection detection NOUN cana-616 100 31 accuracy accuracy NOUN cana-616 100 32 . . PUNCT cana-616 101 1 a a DET cana-616 101 2 detection detection NOUN cana-616 101 3 model model NOUN cana-616 101 4 , , PUNCT cana-616 101 5 really really ADV cana-616 101 6 targeting target VERB cana-616 101 7 recognition recognition NOUN cana-616 101 8 lsd lsd NOUN cana-616 101 9 levels level NOUN cana-616 101 10 , , PUNCT cana-616 101 11 will will AUX cana-616 101 12 be be AUX cana-616 101 13 built build VERB cana-616 101 14 using use VERB cana-616 101 15 deep deep ADJ cana-616 101 16 learning learning NOUN cana-616 101 17 algorithms algorithm NOUN cana-616 101 18 , , PUNCT cana-616 101 19 especially especially ADV cana-616 101 20 including include VERB cana-616 101 21 convolutional convolutional ADJ cana-616 101 22 neural neural ADJ cana-616 101 23 networks network NOUN cana-616 101 24 ( ( PUNCT cana-616 101 25 cnns cnns PROPN cana-616 101 26 ) ) PUNCT cana-616 101 27 , , PUNCT cana-616 101 28 in in ADP cana-616 101 29 this this DET cana-616 101 30 step step NOUN cana-616 101 31 . . PUNCT cana-616 102 1 the the DET cana-616 102 2 suggested suggest VERB cana-616 102 3 iot iot ADJ cana-616 102 4 - - PUNCT cana-616 102 5 enabled enable VERB cana-616 102 6 framework framework NOUN cana-616 102 7 will will AUX cana-616 102 8 have have VERB cana-616 102 9 hardware hardware NOUN cana-616 102 10 and and CCONJ cana-616 102 11 software software NOUN cana-616 102 12 parts part NOUN cana-616 102 13 including include VERB cana-616 102 14 sensors sensor NOUN cana-616 102 15 , , PUNCT cana-616 102 16 actuators actuator NOUN cana-616 102 17 , , PUNCT cana-616 102 18 and and CCONJ cana-616 102 19 a a DET cana-616 102 20 decision decision NOUN cana-616 102 21 - - PUNCT cana-616 102 22 making make VERB cana-616 102 23 unit unit NOUN cana-616 102 24 . . PUNCT cana-616 103 1 the the DET cana-616 103 2 hardware hardware NOUN cana-616 103 3 components component NOUN cana-616 103 4 including include VERB cana-616 103 5 temperature temperature NOUN cana-616 103 6 sensor sensor NOUN cana-616 103 7 , , PUNCT cana-616 103 8 pulse pulse NOUN cana-616 103 9 rate rate NOUN cana-616 103 10 sensor sensor NOUN cana-616 103 11 , , PUNCT cana-616 103 12 and and CCONJ cana-616 103 13 moisture moisture NOUN cana-616 103 14 sensor sensor NOUN cana-616 103 15 will will AUX cana-616 103 16 be be AUX cana-616 103 17 used use VERB cana-616 103 18 to to PART cana-616 103 19 diagnose diagnose VERB cana-616 103 20 lsd lsd NOUN cana-616 103 21 signs sign NOUN cana-616 103 22 in in ADP cana-616 103 23 cows cow NOUN cana-616 103 24 while while SCONJ cana-616 103 25 the the DET cana-616 103 26 power power NOUN cana-616 103 27 supply supply NOUN cana-616 103 28 and and CCONJ cana-616 103 29 lcd lcd NOUN cana-616 103 30 screen screen NOUN cana-616 103 31 will will AUX cana-616 103 32 provide provide VERB cana-616 103 33 prompt prompt ADJ cana-616 103 34 information information NOUN cana-616 103 35 about about ADP cana-616 103 36 the the DET cana-616 103 37 disease disease NOUN cana-616 103 38 . . PUNCT cana-616 104 1 up up ADP cana-616 104 2 to to ADP cana-616 104 3 the the DET cana-616 104 4 software software NOUN cana-616 104 5 end end NOUN cana-616 104 6 , , PUNCT cana-616 104 7 methods method NOUN cana-616 104 8 of of ADP cana-616 104 9 image image NOUN cana-616 104 10 processing processing NOUN cana-616 104 11 will will AUX cana-616 104 12 be be AUX cana-616 104 13 used use VERB cana-616 104 14 and and CCONJ cana-616 104 15 feature feature NOUN cana-616 104 16 extraction extraction NOUN cana-616 104 17 by by ADP cana-616 104 18 the the DET cana-616 104 19 cnns cnn NOUN cana-616 104 20 would would AUX cana-616 104 21 be be AUX cana-616 104 22 employed employ VERB cana-616 104 23 in in ADP cana-616 104 24 analyzing analyze VERB cana-616 104 25 and and CCONJ cana-616 104 26 classifying classify VERB cana-616 104 27 lsd lsd NOUN cana-616 104 28 photos photo NOUN cana-616 104 29 . . PUNCT cana-616 105 1 β€œ " PUNCT cana-616 105 2 the the DET cana-616 105 3 coupling coupling NOUN cana-616 105 4 between between ADP cana-616 105 5 hardware hardware NOUN cana-616 105 6 and and CCONJ cana-616 105 7 software software NOUN cana-616 105 8 units unit NOUN cana-616 105 9 is be AUX cana-616 105 10 purposefully purposefully ADV cana-616 105 11 designed design VERB cana-616 105 12 to to PART cana-616 105 13 perform perform VERB cana-616 105 14 jointly jointly ADV cana-616 105 15 at at ADP cana-616 105 16 peak peak NOUN cana-616 105 17 level level NOUN cana-616 105 18 during during ADP cana-616 105 19 lsd lsd NOUN cana-616 105 20 detection detection NOUN cana-616 105 21 , , PUNCT cana-616 105 22 supervision supervision NOUN cana-616 105 23 and and CCONJ cana-616 105 24 organization organization NOUN cana-616 105 25 ” " PUNCT cana-616 105 26 . . PUNCT cana-616 106 1 in in ADP cana-616 106 2 order order NOUN cana-616 106 3 to to PART cana-616 106 4 be be AUX cana-616 106 5 complete complete ADJ cana-616 106 6 , , PUNCT cana-616 106 7 the the DET cana-616 106 8 device device NOUN cana-616 106 9 will will AUX cana-616 106 10 also also ADV cana-616 106 11 be be AUX cana-616 106 12 connected connect VERB cana-616 106 13 to to ADP cana-616 106 14 the the DET cana-616 106 15 cloud cloud NOUN cana-616 106 16 server server NOUN cana-616 106 17 for for ADP cana-616 106 18 remote remote ADJ cana-616 106 19 monitoring monitoring NOUN cana-616 106 20 data datum NOUN cana-616 106 21 storage storage NOUN cana-616 106 22 . . PUNCT cana-616 107 1 the the DET cana-616 107 2 vessel vessel NOUN cana-616 107 3 " " PUNCT cana-616 107 4 bot bot NOUN cana-616 107 5 " " PUNCT cana-616 107 6 will will AUX cana-616 107 7 become become VERB cana-616 107 8 functional functional ADJ cana-616 107 9 and and CCONJ cana-616 107 10 deliver deliver VERB cana-616 107 11 farmers farmer NOUN cana-616 107 12 the the DET cana-616 107 13 regular regular ADJ cana-616 107 14 health health NOUN cana-616 107 15 parameters parameter NOUN cana-616 107 16 either either CCONJ cana-616 107 17 through through ADP cana-616 107 18 sms sms NOUN cana-616 107 19 - - PUNCT cana-616 107 20 notification notification NOUN cana-616 107 21 or or CCONJ cana-616 107 22 a a DET cana-616 107 23 dedicated dedicated ADJ cana-616 107 24 channel channel NOUN cana-616 107 25 in in ADP cana-616 107 26 telegram telegram NOUN cana-616 107 27 . . PUNCT cana-616 108 1 efficiency efficiency NOUN cana-616 108 2 of of ADP cana-616 108 3 information information NOUN cana-616 108 4 sharing sharing NOUN cana-616 108 5 is be AUX cana-616 108 6 highly highly ADV cana-616 108 7 instigated instigate VERB cana-616 108 8 , , PUNCT cana-616 108 9 this this PRON cana-616 108 10 directly directly ADV cana-616 108 11 ensures ensure VERB cana-616 108 12 timely timely ADJ cana-616 108 13 access access NOUN cana-616 108 14 to to ADP cana-616 108 15 information information NOUN cana-616 108 16 that that PRON cana-616 108 17 can can AUX cana-616 108 18 serve serve VERB cana-616 108 19 as as ADP cana-616 108 20 basis basis NOUN cana-616 108 21 for for ADP cana-616 108 22 disease disease NOUN cana-616 108 23 proactive proactive ADJ cana-616 108 24 management management NOUN cana-616 108 25 and and CCONJ cana-616 108 26 intervention intervention NOUN cana-616 108 27 strategies strategy NOUN cana-616 108 28 . . PUNCT cana-616 109 1 in in ADP cana-616 109 2 general general ADJ cana-616 109 3 , , PUNCT cana-616 109 4 the the DET cana-616 109 5 research research NOUN cana-616 109 6 is be AUX cana-616 109 7 focusing focus VERB cana-616 109 8 on on ADP cana-616 109 9 a a DET cana-616 109 10 sophisticated sophisticated ADJ cana-616 109 11 iot iot NOUN cana-616 109 12 - - PUNCT cana-616 109 13 based base VERB cana-616 109 14 model model NOUN cana-616 109 15 , , PUNCT cana-616 109 16 that that PRON cana-616 109 17 incorporates incorporate VERB cana-616 109 18 image image NOUN cana-616 109 19 processing processing NOUN cana-616 109 20 , , PUNCT cana-616 109 21 deep deep ADJ cana-616 109 22 learning learning NOUN cana-616 109 23 and and CCONJ cana-616 109 24 multi multi ADJ cana-616 109 25 sensor sensor NOUN cana-616 109 26 technology technology NOUN cana-616 109 27 , , PUNCT cana-616 109 28 for for ADP cana-616 109 29 the the DET cana-616 109 30 purpose purpose NOUN cana-616 109 31 of of ADP cana-616 109 32 lsd lsd NOUN cana-616 109 33 prediction prediction NOUN cana-616 109 34 in in ADP cana-616 109 35 cattle cattle NOUN cana-616 109 36 . . PUNCT cana-616 110 1 through through ADP cana-616 110 2 the the DET cana-616 110 3 employment employment NOUN cana-616 110 4 of of ADP cana-616 110 5 hardware hardware NOUN cana-616 110 6 and and CCONJ cana-616 110 7 software software NOUN cana-616 110 8 innovative innovative ADJ cana-616 110 9 means mean NOUN cana-616 110 10 , , PUNCT cana-616 110 11 this this DET cana-616 110 12 frame frame NOUN cana-616 110 13 work work NOUN cana-616 110 14 intends intend VERB cana-616 110 15 to to PART cana-616 110 16 be be AUX cana-616 110 17 the the DET cana-616 110 18 major major ADJ cana-616 110 19 shaper shaper NOUN cana-616 110 20 of of ADP cana-616 110 21 an an DET cana-616 110 22 advanced advanced ADJ cana-616 110 23 lsd lsd NOUN cana-616 110 24 detections detection NOUN cana-616 110 25 and and CCONJ cana-616 110 26 management management NOUN cana-616 110 27 system system NOUN cana-616 110 28 that that PRON cana-616 110 29 would would AUX cana-616 110 30 significantly significantly ADV cana-616 110 31 improve improve VERB cana-616 110 32 animal animal NOUN cana-616 110 33 welfare welfare NOUN cana-616 110 34 and and CCONJ cana-616 110 35 production production NOUN cana-616 110 36 in in ADP cana-616 110 37 livestock livestock NOUN cana-616 110 38 industry industry NOUN cana-616 110 39 . . PUNCT cana-616 111 1 4 4 X cana-616 111 2 . . X cana-616 111 3 an an DET cana-616 111 4 algorithm algorithm NOUN cana-616 111 5 for for ADP cana-616 111 6 advanced advanced ADJ cana-616 111 7 iot iot ADJ cana-616 111 8 - - PUNCT cana-616 111 9 enabled enable VERB cana-616 111 10 detection detection NOUN cana-616 111 11 of of ADP cana-616 111 12 lumpy lumpy ADJ cana-616 111 13 skin skin NOUN cana-616 111 14 disease disease NOUN cana-616 111 15 in in ADP cana-616 111 16 cattle cattle NOUN cana-616 111 17 high high ADJ cana-616 111 18 - - PUNCT cana-616 111 19 level level NOUN cana-616 111 20 algorithm algorithm NOUN cana-616 111 21 outlining outline VERB cana-616 111 22 the the DET cana-616 111 23 steps step NOUN cana-616 111 24 involved involve VERB cana-616 111 25 in in ADP cana-616 111 26 detecting detect VERB cana-616 111 27 lumpy lumpy ADJ cana-616 111 28 skin skin NOUN cana-616 111 29 disease disease NOUN cana-616 111 30 in in ADP cana-616 111 31 cattle cattle NOUN cana-616 111 32 using use VERB cana-616 111 33 an an DET cana-616 111 34 advanced advanced ADJ cana-616 111 35 iot iot ADJ cana-616 111 36 - - PUNCT cana-616 111 37 enabled enable VERB cana-616 111 38 framework framework NOUN cana-616 111 39 : : PUNCT cana-616 111 40 high high ADJ cana-616 111 41 - - PUNCT cana-616 111 42 level level NOUN cana-616 111 43 algorithm algorithm NOUN cana-616 111 44 outlining outline VERB cana-616 111 45 the the DET cana-616 111 46 steps step NOUN cana-616 111 47 involved involve VERB cana-616 111 48 in in ADP cana-616 111 49 detecting detect VERB cana-616 111 50 lumpy lumpy ADJ cana-616 111 51 skin skin NOUN cana-616 111 52 disease disease NOUN cana-616 111 53 in in ADP cana-616 111 54 cattle cattle NOUN cana-616 111 55 using use VERB cana-616 111 56 an an DET cana-616 111 57 advanced advanced ADJ cana-616 111 58 iot iot ADJ cana-616 111 59 - - PUNCT cana-616 111 60 enabled enable VERB cana-616 111 61 framework framework NOUN cana-616 111 62 [ [ X cana-616 111 63 11 11 NUM cana-616 111 64 - - SYM cana-616 111 65 21 21 NUM cana-616 111 66 ] ] PUNCT cana-616 111 67 : : PUNCT cana-616 111 68 image image NOUN cana-616 111 69 collection collection NOUN cana-616 111 70 : : PUNCT cana-616 111 71 collect collect VERB cana-616 111 72 different different ADJ cana-616 111 73 kinds kind NOUN cana-616 111 74 of of ADP cana-616 111 75 pictures picture NOUN cana-616 111 76 portraying portray VERB cana-616 111 77 healthy healthy ADJ cana-616 111 78 and and CCONJ cana-616 111 79 infected infected ADJ cana-616 111 80 cattle cattle NOUN cana-616 111 81 ’s ’s PART cana-616 111 82 skin skin NOUN cana-616 111 83 from from ADP cana-616 111 84 the the DET cana-616 111 85 different different ADJ cana-616 111 86 organizations organization NOUN cana-616 111 87 like like ADP cana-616 111 88 vet vet NOUN cana-616 111 89 clinics clinic NOUN cana-616 111 90 and and CCONJ cana-616 111 91 the the DET cana-616 111 92 online online ADJ cana-616 111 93 digital digital ADJ cana-616 111 94 libraries library NOUN cana-616 111 95 . . PUNCT cana-616 112 1 image image NOUN cana-616 112 2 preprocessing preprocessing NOUN cana-616 112 3 : : PUNCT cana-616 112 4 aim aim VERB cana-616 112 5 for for ADP cana-616 112 6 high high ADJ cana-616 112 7 - - PUNCT cana-616 112 8 quality quality NOUN cana-616 112 9 and and CCONJ cana-616 112 10 consistent consistent ADJ cana-616 112 11 image image NOUN cana-616 112 12 collection collection NOUN cana-616 112 13 by by ADP cana-616 112 14 implementing implement VERB cana-616 112 15 various various ADJ cana-616 112 16 types type NOUN cana-616 112 17 of of ADP cana-616 112 18 preprocessing preprocesse VERB cana-616 112 19 algorithms algorithm NOUN cana-616 112 20 . . PUNCT cana-616 113 1 conduct conduct VERB cana-616 113 2 the the DET cana-616 113 3 following follow VERB cana-616 113 4 operations operation NOUN cana-616 113 5 : : PUNCT cana-616 113 6 removing remove VERB cana-616 113 7 noise noise NOUN cana-616 113 8 , , PUNCT cana-616 113 9 adjusting adjust VERB cana-616 113 10 the the DET cana-616 113 11 contrast contrast NOUN cana-616 113 12 , , PUNCT cana-616 113 13 and and CCONJ cana-616 113 14 resizing resize VERB cana-616 113 15 the the DET cana-616 113 16 data datum NOUN cana-616 113 17 . . PUNCT cana-616 114 1 this this PRON cana-616 114 2 is be AUX cana-616 114 3 aimed aim VERB cana-616 114 4 at at ADP cana-616 114 5 bringing bring VERB cana-616 114 6 the the DET cana-616 114 7 data datum NOUN cana-616 114 8 into into ADP cana-616 114 9 alignment alignment NOUN cana-616 114 10 with with ADP cana-616 114 11 the the DET cana-616 114 12 standard standard NOUN cana-616 114 13 . . PUNCT cana-616 115 1 image image NOUN cana-616 115 2 segmentation segmentation NOUN cana-616 115 3 : : PUNCT cana-616 115 4 partition partition NOUN cana-616 115 5 of of ADP cana-616 115 6 the the DET cana-616 115 7 images image NOUN cana-616 115 8 after after ADP cana-616 115 9 preprocessing preprocesse VERB cana-616 115 10 , , PUNCT cana-616 115 11 just just ADV cana-616 115 12 to to PART cana-616 115 13 get get VERB cana-616 115 14 those those DET cana-616 115 15 areas area NOUN cana-616 115 16 that that PRON cana-616 115 17 are be AUX cana-616 115 18 in in ADP cana-616 115 19 contact contact NOUN cana-616 115 20 with with ADP cana-616 115 21 the the DET cana-616 115 22 cow cow NOUN cana-616 115 23 's 's PART cana-616 115 24 skin skin NOUN cana-616 115 25 . . PUNCT cana-616 116 1 exploit exploit VERB cana-616 116 2 methods method NOUN cana-616 116 3 of of ADP cana-616 116 4 segmentation segmentation NOUN cana-616 116 5 , , PUNCT cana-616 116 6 such such ADJ cana-616 116 7 as as ADP cana-616 116 8 thresholding thresholding NOUN cana-616 116 9 , , PUNCT cana-616 116 10 edge edge NOUN cana-616 116 11 detection detection NOUN cana-616 116 12 or or CCONJ cana-616 116 13 region region NOUN cana-616 116 14 growing grow VERB cana-616 116 15 , , PUNCT cana-616 116 16 to to PART cana-616 116 17 differentiate differentiate VERB cana-616 116 18 between between ADP cana-616 116 19 tumor tumor NOUN cana-616 116 20 edges edge NOUN cana-616 116 21 and and CCONJ cana-616 116 22 surrounding surround VERB cana-616 116 23 tissues tissue NOUN cana-616 116 24 . . PUNCT cana-616 117 1 communications communication NOUN cana-616 117 2 on on ADP cana-616 117 3 applied apply VERB cana-616 117 4 nonlinear nonlinear ADJ cana-616 117 5 analysis analysis NOUN cana-616 117 6 issn issn NOUN cana-616 117 7 : : PUNCT cana-616 117 8 1074 1074 NUM cana-616 117 9 - - PUNCT cana-616 117 10 133x 133x NUM cana-616 117 11 vol vol NOUN cana-616 117 12 31 31 NUM cana-616 117 13 no no NOUN cana-616 117 14 . . PUNCT cana-616 118 1 2s 2s NUM cana-616 118 2 ( ( PUNCT cana-616 118 3 2024 2024 NUM cana-616 118 4 ) ) PUNCT cana-616 118 5 126 126 NUM cana-616 118 6 https://internationalpubls.com https://internationalpubls.com X cana-616 118 7 feature feature NOUN cana-616 118 8 extraction extraction NOUN cana-616 118 9 : : PUNCT cana-616 118 10 segment segment VERB cana-616 118 11 the the DET cana-616 118 12 images image NOUN cana-616 118 13 and and CCONJ cana-616 118 14 then then ADV cana-616 118 15 choose choose VERB cana-616 118 16 the the DET cana-616 118 17 necessary necessary ADJ cana-616 118 18 features feature NOUN cana-616 118 19 to to PART cana-616 118 20 illustrate illustrate VERB cana-616 118 21 features feature NOUN cana-616 118 22 of of ADP cana-616 118 23 lumpy lumpy ADJ cana-616 118 24 skin skin NOUN cana-616 118 25 disease disease NOUN cana-616 118 26 that that PRON cana-616 118 27 we we PRON cana-616 118 28 have have AUX cana-616 118 29 n’t not PART cana-616 118 30 seen see VERB cana-616 118 31 earlier early ADV cana-616 118 32 . . PUNCT cana-616 119 1 implement implement VERB cana-616 119 2 methods method NOUN cana-616 119 3 such such ADJ cana-616 119 4 as as ADP cana-616 119 5 texture texture ADJ cana-616 119 6 analysis analysis NOUN cana-616 119 7 , , PUNCT cana-616 119 8 shape shape NOUN cana-616 119 9 values value NOUN cana-616 119 10 , , PUNCT cana-616 119 11 and and CCONJ cana-616 119 12 color color NOUN cana-616 119 13 histograms histogram NOUN cana-616 119 14 to to PART cana-616 119 15 approximate approximate VERB cana-616 119 16 the the DET cana-616 119 17 drawn draw VERB cana-616 119 18 features feature NOUN cana-616 119 19 . . PUNCT cana-616 120 1 training training NOUN cana-616 120 2 : : PUNCT cana-616 120 3 split split VERB cana-616 120 4 the the DET cana-616 120 5 dataset dataset NOUN cana-616 120 6 into into ADP cana-616 120 7 two two NUM cana-616 120 8 parts part NOUN cana-616 120 9 train train NOUN cana-616 120 10 and and CCONJ cana-616 120 11 validation validation NOUN cana-616 120 12 sets set NOUN cana-616 120 13 . . PUNCT cana-616 121 1 train train VERB cana-616 121 2 the the DET cana-616 121 3 deep deep ADJ cana-616 121 4 learning learning NOUN cana-616 121 5 model model NOUN cana-616 121 6 and and CCONJ cana-616 121 7 use use VERB cana-616 121 8 a a DET cana-616 121 9 cnn cnn NOUN cana-616 121 10 for for ADP cana-616 121 11 instance instance NOUN cana-616 121 12 . . PUNCT cana-616 122 1 the the DET cana-616 122 2 dataset dataset NOUN cana-616 122 3 will will AUX cana-616 122 4 define define VERB cana-616 122 5 the the DET cana-616 122 6 training training NOUN cana-616 122 7 phase phase NOUN cana-616 122 8 . . PUNCT cana-616 123 1 use use VERB cana-616 123 2 techniques technique NOUN cana-616 123 3 like like ADP cana-616 123 4 stochastic stochastic ADJ cana-616 123 5 gradient gradient NOUN cana-616 123 6 decent decent ADJ cana-616 123 7 as as ADV cana-616 123 8 well well ADV cana-616 123 9 as as ADP cana-616 123 10 backpropagation backpropagation NOUN cana-616 123 11 to to PART cana-616 123 12 get get VERB cana-616 123 13 the the DET cana-616 123 14 most most ADJ cana-616 123 15 out out ADP cana-616 123 16 of of ADP cana-616 123 17 the the DET cana-616 123 18 model model NOUN cana-616 123 19 ’s ’s PART cana-616 123 20 parameters parameter NOUN cana-616 123 21 . . PUNCT cana-616 124 1 test test NOUN cana-616 124 2 trained train VERB cana-616 124 3 model model NOUN cana-616 124 4 on on ADP cana-616 124 5 validation validation NOUN cana-616 124 6 data datum NOUN cana-616 124 7 set set VERB cana-616 124 8 for for ADP cana-616 124 9 the the DET cana-616 124 10 purpose purpose NOUN cana-616 124 11 of of ADP cana-616 124 12 evaluation evaluation NOUN cana-616 124 13 its its PRON cana-616 124 14 power power NOUN cana-616 124 15 and and CCONJ cana-616 124 16 ability ability NOUN cana-616 124 17 to to PART cana-616 124 18 generalize generalize VERB cana-616 124 19 . . PUNCT cana-616 125 1 classification classification NOUN cana-616 125 2 : : PUNCT cana-616 125 3 deploy deploy VERB cana-616 125 4 the the DET cana-616 125 5 trained train VERB cana-616 125 6 model model NOUN cana-616 125 7 for for ADP cana-616 125 8 the the DET cana-616 125 9 classification classification NOUN cana-616 125 10 of of ADP cana-616 125 11 new new ADJ cana-616 125 12 and and CCONJ cana-616 125 13 unrelated unrelated ADJ cana-616 125 14 image image NOUN cana-616 125 15 as as ADP cana-616 125 16 either either ADV cana-616 125 17 , , PUNCT cana-616 125 18 healthy healthy ADJ cana-616 125 19 or or CCONJ cana-616 125 20 having having AUX cana-616 125 21 lumpy lumpy VERB cana-616 125 22 skin skin NOUN cana-616 125 23 disease disease NOUN cana-616 125 24 . . PUNCT cana-616 126 1 put put VERB cana-616 126 2 through through ADP cana-616 126 3 the the DET cana-616 126 4 model model NOUN cana-616 126 5 the the DET cana-616 126 6 edited edited ADJ cana-616 126 7 and and CCONJ cana-616 126 8 sliced slice VERB cana-616 126 9 images image NOUN cana-616 126 10 . . PUNCT cana-616 127 1 using use VERB cana-616 127 2 the the DET cana-616 127 3 model model NOUN cana-616 127 4 output output NOUN cana-616 127 5 we we PRON cana-616 127 6 get get VERB cana-616 127 7 the the DET cana-616 127 8 data datum NOUN cana-616 127 9 , , PUNCT cana-616 127 10 which which PRON cana-616 127 11 consists consist VERB cana-616 127 12 of of ADP cana-616 127 13 probability probability NOUN cana-616 127 14 scores score NOUN cana-616 127 15 or or CCONJ cana-616 127 16 class class NOUN cana-616 127 17 label label NOUN cana-616 127 18 . . PUNCT cana-616 128 1 based base VERB cana-616 128 2 on on ADP cana-616 128 3 it it PRON cana-616 128 4 we we PRON cana-616 128 5 classify classify VERB cana-616 128 6 , , PUNCT cana-616 128 7 the the DET cana-616 128 8 images image NOUN cana-616 128 9 correctly correctly ADV cana-616 128 10 . . PUNCT cana-616 129 1 iot iot ADJ cana-616 129 2 integration integration NOUN cana-616 129 3 : : PUNCT cana-616 129 4 put put VERB cana-616 129 5 in in ADP cana-616 129 6 a a DET cana-616 129 7 place place NOUN cana-616 129 8 a a DET cana-616 129 9 model model NOUN cana-616 129 10 that that PRON cana-616 129 11 will will AUX cana-616 129 12 combine combine VERB cana-616 129 13 the the DET cana-616 129 14 detection detection NOUN cana-616 129 15 model model NOUN cana-616 129 16 and and CCONJ cana-616 129 17 the the DET cana-616 129 18 iot iot NOUN cana-616 129 19 devices device NOUN cana-616 129 20 as as ADV cana-616 129 21 well well ADV cana-616 129 22 as as ADP cana-616 129 23 the the DET cana-616 129 24 sensors sensor NOUN cana-616 129 25 for for ADP cana-616 129 26 real real ADJ cana-616 129 27 time time NOUN cana-616 129 28 monitoring monitoring NOUN cana-616 129 29 of of ADP cana-616 129 30 the the DET cana-616 129 31 cattle cattle NOUN cana-616 129 32 health health NOUN cana-616 129 33 . . PUNCT cana-616 130 1 aim aim AUX cana-616 130 2 - - PUNCT cana-616 130 3 to to PART cana-616 130 4 roll roll VERB cana-616 130 5 it it PRON cana-616 130 6 out out ADP cana-616 130 7 on on ADP cana-616 130 8 edge edge NOUN cana-616 130 9 devices device NOUN cana-616 130 10 and and CCONJ cana-616 130 11 cloud cloud NOUN cana-616 130 12 platforms platform NOUN cana-616 130 13 in in ADP cana-616 130 14 order order NOUN cana-616 130 15 to to PART cana-616 130 16 ensure ensure VERB cana-616 130 17 remote remote ADJ cana-616 130 18 access access NOUN cana-616 130 19 and and CCONJ cana-616 130 20 feasibility feasibility NOUN cana-616 130 21 of of ADP cana-616 130 22 scaling scale VERB cana-616 130 23 the the DET cana-616 130 24 solution solution NOUN cana-616 130 25 . . PUNCT cana-616 131 1 implement implement VERB cana-616 131 2 the the DET cana-616 131 3 sensor sensor NOUN cana-616 131 4 networks network VERB cana-616 131 5 wirelessly wirelessly ADV cana-616 131 6 to to PART cana-616 131 7 get get VERB cana-616 131 8 the the DET cana-616 131 9 animal animal NOUN cana-616 131 10 ’s ’s PART cana-616 131 11 primary primary ADJ cana-616 131 12 health health NOUN cana-616 131 13 parameters parameter NOUN cana-616 131 14 which which PRON cana-616 131 15 include include VERB cana-616 131 16 temperature temperature NOUN cana-616 131 17 and and CCONJ cana-616 131 18 the the DET cana-616 131 19 heart heart NOUN cana-616 131 20 rate rate NOUN cana-616 131 21 . . PUNCT cana-616 132 1 alerting alert VERB cana-616 132 2 mechanism mechanism NOUN cana-616 132 3 : : PUNCT cana-616 132 4 likewise likewise ADV cana-616 132 5 , , PUNCT cana-616 132 6 incorporating incorporate VERB cana-616 132 7 an an DET cana-616 132 8 alerting alerting ADJ cana-616 132 9 mechanism mechanism NOUN cana-616 132 10 to to PART cana-616 132 11 alert alert VERB cana-616 132 12 farmers farmer NOUN cana-616 132 13 / / SYM cana-616 132 14 veterinarians veterinarian NOUN cana-616 132 15 of of ADP cana-616 132 16 any any DET cana-616 132 17 outbreak outbreak NOUN cana-616 132 18 of of ADP cana-616 132 19 lumpy lumpy ADJ cana-616 132 20 skin skin NOUN cana-616 132 21 disease disease NOUN cana-616 132 22 should should AUX cana-616 132 23 be be AUX cana-616 132 24 put put VERB cana-616 132 25 in in ADP cana-616 132 26 place place NOUN cana-616 132 27 . . PUNCT cana-616 133 1 identify identify VERB cana-616 133 2 the the DET cana-616 133 3 boundaries boundary NOUN cana-616 133 4 of of ADP cana-616 133 5 unusual unusual ADJ cana-616 133 6 health health NOUN cana-616 133 7 parameters parameter NOUN cana-616 133 8 and and CCONJ cana-616 133 9 sound sound VERB cana-616 133 10 an an DET cana-616 133 11 alarm alarm NOUN cana-616 133 12 signal signal NOUN cana-616 133 13 when when SCONJ cana-616 133 14 these these DET cana-616 133 15 boundaries boundary NOUN cana-616 133 16 are be AUX cana-616 133 17 transgressed transgress VERB cana-616 133 18 . . PUNCT cana-616 134 1 issue issue NOUN cana-616 134 2 alerts alert NOUN cana-616 134 3 via via ADP cana-616 134 4 sms sms PROPN cana-616 134 5 , , PUNCT cana-616 134 6 e e NOUN cana-616 134 7 - - NOUN cana-616 134 8 mail mail NOUN cana-616 134 9 , , PUNCT cana-616 134 10 or or CCONJ cana-616 134 11 push push VERB cana-616 134 12 notifications notification NOUN cana-616 134 13 to to PART cana-616 134 14 make make VERB cana-616 134 15 sure sure ADJ cana-616 134 16 health health NOUN cana-616 134 17 care care NOUN cana-616 134 18 providers provider NOUN cana-616 134 19 give give VERB cana-616 134 20 the the DET cana-616 134 21 appropriate appropriate ADJ cana-616 134 22 aid aid NOUN cana-616 134 23 and and CCONJ cana-616 134 24 disease disease NOUN cana-616 134 25 management management NOUN cana-616 134 26 . . PUNCT cana-616 135 1 continuous continuous ADJ cana-616 135 2 monitoring monitoring NOUN cana-616 135 3 and and CCONJ cana-616 135 4 refinement refinement NOUN cana-616 135 5 : : PUNCT cana-616 135 6 it it PRON cana-616 135 7 's be AUX cana-616 135 8 essential essential ADJ cana-616 135 9 to to PART cana-616 135 10 continuously continuously ADV cana-616 135 11 monitor monitor VERB cana-616 135 12 how how SCONJ cana-616 135 13 a a DET cana-616 135 14 detection detection NOUN cana-616 135 15 system system NOUN cana-616 135 16 performs perform VERB cana-616 135 17 in in ADP cana-616 135 18 real real ADJ cana-616 135 19 world world NOUN cana-616 135 20 settings setting NOUN cana-616 135 21 . . PUNCT cana-616 136 1 seek seek VERB cana-616 136 2 the the DET cana-616 136 3 users user NOUN cana-616 136 4 ' ' PART cana-616 136 5 opinions opinion NOUN cana-616 136 6 and and CCONJ cana-616 136 7 the the DET cana-616 136 8 concerns concern NOUN cana-616 136 9 of of ADP cana-616 136 10 stakeholders stakeholder NOUN cana-616 136 11 to to PART cana-616 136 12 discover discover VERB cana-616 136 13 areas area NOUN cana-616 136 14 for for ADP cana-616 136 15 improvement improvement NOUN cana-616 136 16 so so SCONJ cana-616 136 17 as as ADP cana-616 136 18 to to ADP cana-616 136 19 fine fine ADJ cana-616 136 20 - - PUNCT cana-616 136 21 tune tune NOUN cana-616 136 22 it it PRON cana-616 136 23 . . PUNCT cana-616 137 1 to to PART cana-616 137 2 improve improve VERB cana-616 137 3 the the DET cana-616 137 4 model model NOUN cana-616 137 5 performance performance NOUN cana-616 137 6 in in ADP cana-616 137 7 future future NOUN cana-616 137 8 , , PUNCT cana-616 137 9 we we PRON cana-616 137 10 are be AUX cana-616 137 11 planning plan VERB cana-616 137 12 to to PART cana-616 137 13 introduce introduce VERB cana-616 137 14 new new ADJ cana-616 137 15 data datum NOUN cana-616 137 16 and and CCONJ cana-616 137 17 update update VERB cana-616 137 18 the the DET cana-616 137 19 algorithm algorithm NOUN cana-616 137 20 in in ADP cana-616 137 21 a a DET cana-616 137 22 regular regular ADJ cana-616 137 23 basis basis NOUN cana-616 137 24 ensuring ensure VERB cana-616 137 25 that that SCONJ cana-616 137 26 the the DET cana-616 137 27 desired desire VERB cana-616 137 28 accuracy accuracy NOUN cana-616 137 29 and and CCONJ cana-616 137 30 reliability reliability NOUN cana-616 137 31 is be AUX cana-616 137 32 achieved achieve VERB cana-616 137 33 in in ADP cana-616 137 34 real real ADJ cana-616 137 35 time time NOUN cana-616 137 36 . . PUNCT cana-616 138 1 this this DET cana-616 138 2 algorithm algorithm NOUN cana-616 138 3 - - PUNCT cana-616 138 4 based base VERB cana-616 138 5 strategy strategy NOUN cana-616 138 6 can can AUX cana-616 138 7 then then ADV cana-616 138 8 enable enable VERB cana-616 138 9 the the DET cana-616 138 10 entire entire ADJ cana-616 138 11 advanced advanced ADJ cana-616 138 12 iot iot ADJ cana-616 138 13 - - PUNCT cana-616 138 14 enabled enable VERB cana-616 138 15 system system NOUN cana-616 138 16 to to PART cana-616 138 17 accurately accurately ADV cana-616 138 18 detect detect VERB cana-616 138 19 abnormal abnormal ADJ cana-616 138 20 skin skin NOUN cana-616 138 21 conditions condition NOUN cana-616 138 22 in in ADP cana-616 138 23 cattle cattle NOUN cana-616 138 24 and and CCONJ cana-616 138 25 provide provide VERB cana-616 138 26 an an DET cana-616 138 27 early early ADJ cana-616 138 28 warning warning NOUN cana-616 138 29 sign sign NOUN cana-616 138 30 appropriate appropriate ADJ cana-616 138 31 to to PART cana-616 138 32 respond respond VERB cana-616 138 33 which which PRON cana-616 138 34 could could AUX cana-616 138 35 save save VERB cana-616 138 36 livestock livestock NOUN cana-616 138 37 health health NOUN cana-616 138 38 and and CCONJ cana-616 138 39 productivity productivity NOUN cana-616 138 40 from from ADP cana-616 138 41 the the DET cana-616 138 42 disease disease NOUN cana-616 138 43 . . PUNCT cana-616 139 1 5 5 X cana-616 139 2 . . X cana-616 139 3 methodology methodology NOUN cana-616 139 4 integrating integrate VERB cana-616 139 5 advanced advanced ADJ cana-616 139 6 mathematical mathematical ADJ cana-616 139 7 formulations formulation NOUN cana-616 139 8 such such ADJ cana-616 139 9 as as ADP cana-616 139 10 bayesian bayesian NOUN cana-616 139 11 optimization optimization NOUN cana-616 139 12 , , PUNCT cana-616 139 13 gradient gradient NOUN cana-616 139 14 and and CCONJ cana-616 139 15 hessian hessian ADJ cana-616 139 16 computations computation NOUN cana-616 139 17 , , PUNCT cana-616 139 18 and and CCONJ cana-616 139 19 sophisticated sophisticated ADJ cana-616 139 20 model model NOUN cana-616 139 21 evaluation evaluation NOUN cana-616 139 22 metrics metric NOUN cana-616 139 23 with with ADP cana-616 139 24 the the DET cana-616 139 25 random random ADJ cana-616 139 26 forest forest NOUN cana-616 139 27 classifier classifier NOUN cana-616 139 28 can can AUX cana-616 139 29 significantly significantly ADV cana-616 139 30 enhance enhance VERB cana-616 139 31 the the DET cana-616 139 32 model model NOUN cana-616 139 33 ’s ’s PART cana-616 139 34 accuracy accuracy NOUN cana-616 139 35 , , PUNCT cana-616 139 36 especially especially ADV cana-616 139 37 in in ADP cana-616 139 38 complex complex ADJ cana-616 139 39 , , PUNCT cana-616 139 40 non non ADJ cana-616 139 41 - - ADJ cana-616 139 42 linear linear ADJ cana-616 139 43 classification classification NOUN cana-616 139 44 tasks task NOUN cana-616 139 45 like like ADP cana-616 139 46 image image NOUN cana-616 139 47 - - PUNCT cana-616 139 48 based base VERB cana-616 139 49 disease disease NOUN cana-616 139 50 detection detection NOUN cana-616 139 51 . . PUNCT cana-616 140 1 this this DET cana-616 140 2 comprehensive comprehensive ADJ cana-616 140 3 explanation explanation NOUN cana-616 140 4 , , PUNCT cana-616 140 5 structured structure VERB cana-616 140 6 around around ADP cana-616 140 7 the the DET cana-616 140 8 15 15 NUM cana-616 140 9 equations equation NOUN cana-616 140 10 provided provide VERB cana-616 140 11 earlier early ADV cana-616 140 12 , , PUNCT cana-616 140 13 will will AUX cana-616 140 14 elucidate elucidate VERB cana-616 140 15 how how SCONJ cana-616 140 16 these these DET cana-616 140 17 elements element NOUN cana-616 140 18 synergize synergize VERB cana-616 140 19 to to PART cana-616 140 20 refine refine VERB cana-616 140 21 a a DET cana-616 140 22 random random ADJ cana-616 140 23 forest forest NOUN cana-616 140 24 model model NOUN cana-616 140 25 . . PUNCT cana-616 141 1 foundation foundation NOUN cana-616 141 2 of of ADP cana-616 141 3 random random ADJ cana-616 141 4 forest forest NOUN cana-616 141 5 and and CCONJ cana-616 141 6 its its PRON cana-616 141 7 enhancements enhancement NOUN cana-616 141 8 random random ADJ cana-616 141 9 forest forest NOUN cana-616 141 10 ( ( PUNCT cana-616 141 11 rf rf NOUN cana-616 141 12 ) ) PUNCT cana-616 141 13 is be AUX cana-616 141 14 an an DET cana-616 141 15 ensemble ensemble ADJ cana-616 141 16 learning learning NOUN cana-616 141 17 method method NOUN cana-616 141 18 known know VERB cana-616 141 19 for for ADP cana-616 141 20 its its PRON cana-616 141 21 robustness robustness NOUN cana-616 141 22 and and CCONJ cana-616 141 23 effectiveness effectiveness NOUN cana-616 141 24 across across ADP cana-616 141 25 various various ADJ cana-616 141 26 applications application NOUN cana-616 141 27 . . PUNCT cana-616 142 1 it it PRON cana-616 142 2 operates operate VERB cana-616 142 3 by by ADP cana-616 142 4 constructing construct VERB cana-616 142 5 a a DET cana-616 142 6 multitude multitude NOUN cana-616 142 7 of of ADP cana-616 142 8 decision decision NOUN cana-616 142 9 trees tree NOUN cana-616 142 10 at at ADP cana-616 142 11 training training NOUN cana-616 142 12 time time NOUN cana-616 142 13 communications communication NOUN cana-616 142 14 on on ADP cana-616 142 15 applied apply VERB cana-616 142 16 nonlinear nonlinear ADJ cana-616 142 17 analysis analysis NOUN cana-616 142 18 issn issn NOUN cana-616 142 19 : : PUNCT cana-616 142 20 1074 1074 NUM cana-616 142 21 - - PUNCT cana-616 142 22 133x 133x NUM cana-616 142 23 vol vol NOUN cana-616 142 24 31 31 NUM cana-616 142 25 no no NOUN cana-616 142 26 . . PUNCT cana-616 143 1 2s 2s NUM cana-616 143 2 ( ( PUNCT cana-616 143 3 2024 2024 NUM cana-616 143 4 ) ) PUNCT cana-616 143 5 127 127 NUM cana-616 143 6 https://internationalpubls.com https://internationalpubls.com X cana-616 143 7 and and CCONJ cana-616 143 8 outputting output VERB cana-616 143 9 the the DET cana-616 143 10 class class NOUN cana-616 143 11 that that PRON cana-616 143 12 is be AUX cana-616 143 13 the the DET cana-616 143 14 mode mode NOUN cana-616 143 15 of of ADP cana-616 143 16 the the DET cana-616 143 17 classes class NOUN cana-616 143 18 ( ( PUNCT cana-616 143 19 classification classification NOUN cana-616 143 20 ) ) PUNCT cana-616 143 21 or or CCONJ cana-616 143 22 mean mean ADJ cana-616 143 23 prediction prediction NOUN cana-616 143 24 ( ( PUNCT cana-616 143 25 regression regression NOUN cana-616 143 26 ) ) PUNCT cana-616 143 27 of of ADP cana-616 143 28 the the DET cana-616 143 29 individual individual ADJ cana-616 143 30 trees tree NOUN cana-616 143 31 . . PUNCT cana-616 144 1 1 1 X cana-616 144 2 . . X cana-616 144 3 basic basic ADJ cana-616 144 4 algorithm algorithm NOUN cana-616 144 5 modifications modification NOUN cana-616 144 6 : : PUNCT cana-616 144 7 β€’ β€’ NUM cana-616 144 8 entropy entropy PROPN cana-616 144 9 and and CCONJ cana-616 144 10 gini gini PROPN cana-616 144 11 impurity impurity NOUN cana-616 144 12 ( ( PUNCT cana-616 144 13 equations equation NOUN cana-616 144 14 1 1 NUM cana-616 144 15 - - SYM cana-616 144 16 3 3 NUM cana-616 144 17 ) ) PUNCT cana-616 144 18 are be AUX cana-616 144 19 crucial crucial ADJ cana-616 144 20 for for ADP cana-616 144 21 constructing construct VERB cana-616 144 22 the the DET cana-616 144 23 decision decision NOUN cana-616 144 24 trees tree NOUN cana-616 144 25 within within ADP cana-616 144 26 a a DET cana-616 144 27 rf rf NOUN cana-616 144 28 . . PUNCT cana-616 144 29 by by ADP cana-616 144 30 optimizing optimize VERB cana-616 144 31 the the DET cana-616 144 32 criteria criterion NOUN cana-616 144 33 for for ADP cana-616 144 34 splitting splitting NOUN cana-616 144 35 nodes node NOUN cana-616 144 36 , , PUNCT cana-616 144 37 we we PRON cana-616 144 38 can can AUX cana-616 144 39 ensure ensure VERB cana-616 144 40 that that SCONJ cana-616 144 41 the the DET cana-616 144 42 trees tree NOUN cana-616 144 43 are be AUX cana-616 144 44 as as ADV cana-616 144 45 informative informative ADJ cana-616 144 46 and and CCONJ cana-616 144 47 discriminative discriminative NOUN cana-616 144 48 as as ADP cana-616 144 49 possible possible ADJ cana-616 144 50 . . PUNCT cana-616 145 1 β€’ β€’ NUM cana-616 145 2 incorporating incorporate VERB cana-616 145 3 gradient gradient NOUN cana-616 145 4 and and CCONJ cana-616 145 5 hessian hessian ADJ cana-616 145 6 computations computation NOUN cana-616 145 7 ( ( PUNCT cana-616 145 8 equations equation NOUN cana-616 145 9 13 13 NUM cana-616 145 10 - - SYM cana-616 145 11 14 14 NUM cana-616 145 12 ) ) PUNCT cana-616 145 13 into into ADP cana-616 145 14 the the DET cana-616 145 15 training training NOUN cana-616 145 16 process process NOUN cana-616 145 17 of of ADP cana-616 145 18 each each DET cana-616 145 19 tree tree NOUN cana-616 145 20 within within ADP cana-616 145 21 the the DET cana-616 145 22 rf rf NOUN cana-616 145 23 can can AUX cana-616 145 24 help help VERB cana-616 145 25 in in ADP cana-616 145 26 precisely precisely ADV cana-616 145 27 navigating navigate VERB cana-616 145 28 the the DET cana-616 145 29 parameter parameter NOUN cana-616 145 30 space space NOUN cana-616 145 31 , , PUNCT cana-616 145 32 thus thus ADV cana-616 145 33 optimizing optimize VERB cana-616 145 34 splits split NOUN cana-616 145 35 that that PRON cana-616 145 36 reduce reduce VERB cana-616 145 37 overfitting overfitte VERB cana-616 145 38 and and CCONJ cana-616 145 39 improve improve VERB cana-616 145 40 generalization generalization NOUN cana-616 145 41 . . PUNCT cana-616 146 1 bayesian bayesian NOUN cana-616 146 2 optimization optimization NOUN cana-616 146 3 for for ADP cana-616 146 4 hyperparameter hyperparameter NOUN cana-616 146 5 tuning tune VERB cana-616 146 6 bayesian bayesian NOUN cana-616 146 7 optimization optimization NOUN cana-616 146 8 ( ( PUNCT cana-616 146 9 bo bo PROPN cana-616 146 10 ) ) PUNCT cana-616 146 11 is be AUX cana-616 146 12 a a DET cana-616 146 13 strategy strategy NOUN cana-616 146 14 for for ADP cana-616 146 15 global global ADJ cana-616 146 16 optimization optimization NOUN cana-616 146 17 of of ADP cana-616 146 18 noisy noisy ADJ cana-616 146 19 black black ADJ cana-616 146 20 - - PUNCT cana-616 146 21 box box NOUN cana-616 146 22 functions function NOUN cana-616 146 23 . . PUNCT cana-616 147 1 it it PRON cana-616 147 2 ’s ’ VERB cana-616 147 3 particularly particularly ADV cana-616 147 4 useful useful ADJ cana-616 147 5 for for ADP cana-616 147 6 rf rf ADJ cana-616 147 7 due due ADP cana-616 147 8 to to ADP cana-616 147 9 the the DET cana-616 147 10 typically typically ADV cana-616 147 11 high high ADJ cana-616 147 12 - - PUNCT cana-616 147 13 dimensional dimensional ADJ cana-616 147 14 and and CCONJ cana-616 147 15 complex complex ADJ cana-616 147 16 hyperparameter hyperparameter NOUN cana-616 147 17 space space NOUN cana-616 147 18 ( ( PUNCT cana-616 147 19 e.g. e.g. ADV cana-616 147 20 , , PUNCT cana-616 147 21 number number NOUN cana-616 147 22 of of ADP cana-616 147 23 trees tree NOUN cana-616 147 24 , , PUNCT cana-616 147 25 max max NOUN cana-616 147 26 depth depth NOUN cana-616 147 27 of of ADP cana-616 147 28 trees tree NOUN cana-616 147 29 , , PUNCT cana-616 147 30 min min NOUN cana-616 147 31 samples sample NOUN cana-616 147 32 split split VERB cana-616 147 33 ) ) PUNCT cana-616 147 34 . . PUNCT cana-616 148 1 knowledge knowledge NOUN cana-616 148 2 gradient gradient NOUN cana-616 148 3 𝐾𝐺(π‘₯ 𝐾𝐺(π‘₯ NOUN cana-616 148 4 ) ) PUNCT cana-616 148 5 βˆ’ βˆ’ NOUN cana-616 148 6 π”Όπ‘Œπ‘₯ π”Όπ‘Œπ‘₯ NOUN cana-616 149 1 [ [ X cana-616 149 2 max max NOUN cana-616 149 3 π‘₯β€² π‘₯β€² PUNCT cana-616 149 4 β€Š β€Š SPACE cana-616 149 5 πœ‡π‘›+1(π‘₯ πœ‡π‘›+1(π‘₯ PROPN cana-616 149 6 β€² β€² PROPN cana-616 149 7 ) ) PUNCT cana-616 149 8 ∣ ∣ NOUN cana-616 149 9 π‘Œπ‘₯ π‘Œπ‘₯ PROPN cana-616 149 10 βˆ’ βˆ’ PROPN cana-616 149 11 𝑦 𝑦 NOUN cana-616 149 12 ] ] X cana-616 149 13 βˆ’ βˆ’ PROPN cana-616 149 14 max max PROPN cana-616 149 15 π‘₯β€² π‘₯β€² PUNCT cana-616 149 16 β€Š β€Š SPACE cana-616 149 17 πœ‡π‘›(π‘₯ πœ‡π‘›(π‘₯ PUNCT cana-616 149 18 β€² β€² NOUN cana-616 149 19 ) ) PUNCT cana-616 149 20 ( ( PUNCT cana-616 149 21 23 23 NUM cana-616 149 22 ) ) PUNCT cana-616 149 23 the the DET cana-616 149 24 knowledge knowledge NOUN cana-616 149 25 gradient gradient NOUN cana-616 149 26 is be AUX cana-616 149 27 used use VERB cana-616 149 28 for for ADP cana-616 149 29 sequential sequential ADJ cana-616 149 30 decision decision NOUN cana-616 149 31 processes process NOUN cana-616 149 32 , , PUNCT cana-616 149 33 where where SCONJ cana-616 149 34 π‘Œπ‘§ π‘Œπ‘§ PROPN cana-616 149 35 is be AUX cana-616 149 36 the the DET cana-616 149 37 observation observation NOUN cana-616 149 38 at at ADP cana-616 149 39 point point NOUN cana-616 149 40 π‘₯ π‘₯ NOUN cana-616 149 41 and and CCONJ cana-616 149 42 πœ‡π‘› πœ‡π‘› PROPN cana-616 149 43 is be AUX cana-616 149 44 the the DET cana-616 149 45 current current ADJ cana-616 149 46 belief belief NOUN cana-616 149 47 model model NOUN cana-616 149 48 . . PUNCT cana-616 150 1 entropy entropy PROPN cana-616 150 2 search search PROPN cana-616 150 3 pes⁑(π‘₯ pes⁑(π‘₯ NUM cana-616 150 4 ) ) PUNCT cana-616 151 1 βˆ’ βˆ’ PROPN cana-616 151 2 𝐻[𝑝(π‘“βˆ— 𝐻[𝑝(π‘“βˆ— NOUN cana-616 151 3 ∣ ∣ PROPN cana-616 151 4 𝐷𝑛 𝐷𝑛 NOUN cana-616 151 5 ) ) PUNCT cana-616 151 6 ] ] PUNCT cana-616 152 1 βˆ’ βˆ’ PROPN cana-616 152 2 π”Όπ‘Œπ‘₯[𝐻[𝑝(𝑓 π”Όπ‘Œπ‘₯[𝐻[𝑝(𝑓 PROPN cana-616 152 3 βˆ— βˆ— X cana-616 152 4 ∣ ∣ PROPN cana-616 152 5 𝐷𝑛+1 𝐷𝑛+1 NOUN cana-616 152 6 ) ) PUNCT cana-616 152 7 ] ] PUNCT cana-616 152 8 ] ] X cana-616 152 9 ( ( PUNCT cana-616 152 10 24 24 NUM cana-616 152 11 ) ) PUNCT cana-616 152 12 predictive predictive ADJ cana-616 152 13 entropy entropy NOUN cana-616 152 14 search search NOUN cana-616 152 15 aims aim VERB cana-616 152 16 to to PART cana-616 152 17 reduce reduce VERB cana-616 152 18 the the DET cana-616 152 19 entropy entropy NOUN cana-616 152 20 of of ADP cana-616 152 21 the the DET cana-616 152 22 distribution distribution NOUN cana-616 152 23 over over ADP cana-616 152 24 the the DET cana-616 152 25 global global ADJ cana-616 152 26 minimum minimum NOUN cana-616 152 27 , , PUNCT cana-616 152 28 enhancing enhance VERB cana-616 152 29 the the DET cana-616 152 30 exploratory exploratory ADJ cana-616 152 31 capabilities capability NOUN cana-616 152 32 of of ADP cana-616 152 33 the the DET cana-616 152 34 optimization optimization NOUN cana-616 152 35 process process NOUN cana-616 152 36 . . PUNCT cana-616 153 1 advanced advanced ADJ cana-616 153 2 matrix matrix NOUN cana-616 153 3 operations operation NOUN cana-616 153 4 in in ADP cana-616 153 5 gaussian gaussian ADJ cana-616 153 6 processes process NOUN cana-616 153 7 cholesky cholesky ADJ cana-616 153 8 decomposition decomposition NOUN cana-616 153 9 for for ADP cana-616 153 10 gp gp NOUN cana-616 153 11 𝐾 𝐾 NOUN cana-616 153 12 βˆ’ βˆ’ PROPN cana-616 153 13 𝐿𝐿𝑇 𝐿𝐿𝑇 PROPN cana-616 153 14 where where SCONJ cana-616 153 15 𝐿 𝐿 PROPN cana-616 153 16 is be AUX cana-616 153 17 the the DET cana-616 153 18 lower low ADJ cana-616 153 19 triangular triangular NOUN cana-616 153 20 matrix matrix NOUN cana-616 153 21 resulting result VERB cana-616 153 22 from from ADP cana-616 153 23 the the DET cana-616 153 24 cholesky cholesky ADJ cana-616 153 25 decomposition decomposition NOUN cana-616 153 26 of of ADP cana-616 153 27 the the DET cana-616 153 28 covariance covariance NOUN cana-616 153 29 matrix matrix NOUN cana-616 153 30 𝐾 𝐾 PROPN cana-616 153 31 , , PUNCT cana-616 153 32 used use VERB cana-616 153 33 to to PART cana-616 153 34 solve solve VERB cana-616 153 35 for for ADP cana-616 153 36 gaussian gaussian ADJ cana-616 153 37 processes process NOUN cana-616 153 38 efficiently efficiently ADV cana-616 153 39 . . PUNCT cana-616 154 1 inverse inverse NOUN cana-616 154 2 of of ADP cana-616 154 3 covariance covariance NOUN cana-616 154 4 matrix matrix NOUN cana-616 154 5 πΎβˆ’1 πΎβˆ’1 ADP cana-616 154 6 βˆ’ βˆ’ PROPN cana-616 155 1 ( ( PUNCT cana-616 155 2 𝐿𝐿𝑇)βˆ’1 𝐿𝐿𝑇)βˆ’1 VERB cana-616 155 3 this this DET cana-616 155 4 equation equation NOUN cana-616 155 5 helps help VERB cana-616 155 6 in in ADP cana-616 155 7 the the DET cana-616 155 8 computation computation NOUN cana-616 155 9 of of ADP cana-616 155 10 the the DET cana-616 155 11 predictive predictive ADJ cana-616 155 12 distribution distribution NOUN cana-616 155 13 where where SCONJ cana-616 155 14 direct direct ADJ cana-616 155 15 inversion inversion NOUN cana-616 155 16 of of ADP cana-616 155 17 𝐾 𝐾 PROPN cana-616 155 18 is be AUX cana-616 155 19 computationally computationally ADV cana-616 155 20 expensive expensive ADJ cana-616 155 21 . . PUNCT cana-616 156 1 model model NOUN cana-616 156 2 complexity complexity NOUN cana-616 156 3 and and CCONJ cana-616 156 4 error error NOUN cana-616 156 5 trade trade NOUN cana-616 156 6 - - PUNCT cana-616 156 7 off off ADP cana-616 156 8 bias bias NOUN cana-616 156 9 - - PUNCT cana-616 156 10 variance variance NOUN cana-616 156 11 decomposition decomposition NOUN cana-616 156 12 communications communication NOUN cana-616 156 13 on on ADP cana-616 156 14 applied apply VERB cana-616 156 15 nonlinear nonlinear ADJ cana-616 156 16 analysis analysis NOUN cana-616 156 17 issn issn NOUN cana-616 156 18 : : PUNCT cana-616 156 19 1074 1074 NUM cana-616 156 20 - - PUNCT cana-616 156 21 133x 133x NUM cana-616 156 22 vol vol NOUN cana-616 156 23 31 31 NUM cana-616 156 24 no no NOUN cana-616 156 25 . . PUNCT cana-616 157 1 2s 2s NUM cana-616 157 2 ( ( PUNCT cana-616 157 3 2024 2024 NUM cana-616 157 4 ) ) PUNCT cana-616 157 5 128 128 NUM cana-616 157 6 https://internationalpubls.com https://internationalpubls.com X cana-616 157 7 err⁑(π‘₯ err⁑(π‘₯ PROPN cana-616 157 8 ) ) PUNCT cana-616 157 9 = = SYM cana-616 157 10 ( ( PUNCT cana-616 157 11 .bias .bias ADP cana-616 157 12 ⁑2 ⁑2 NOUN cana-616 157 13 + + NUM cana-616 157 14 variance variance NOUN cana-616 157 15 + + NOUN cana-616 157 16 𝜎2 𝜎2 NOUN cana-616 157 17 ) ) PUNCT cana-616 157 18 this this DET cana-616 157 19 fundamental fundamental ADJ cana-616 157 20 decomposition decomposition NOUN cana-616 157 21 helps help VERB cana-616 157 22 in in ADP cana-616 157 23 understanding understand VERB cana-616 157 24 how how SCONJ cana-616 157 25 different different ADJ cana-616 157 26 errors error NOUN cana-616 157 27 contribute contribute VERB cana-616 157 28 to to ADP cana-616 157 29 the the DET cana-616 157 30 overall overall ADJ cana-616 157 31 error error NOUN cana-616 157 32 in in ADP cana-616 157 33 predictions prediction NOUN cana-616 157 34 , , PUNCT cana-616 157 35 guiding guide VERB cana-616 157 36 model model NOUN cana-616 157 37 complexity complexity NOUN cana-616 157 38 decisions decision NOUN cana-616 157 39 . . PUNCT cana-616 158 1 learning learn VERB cana-616 158 2 dynamics dynamic NOUN cana-616 158 3 exponential exponential ADJ cana-616 158 4 decay decay NOUN cana-616 158 5 learning learn VERB cana-616 158 6 rate rate NOUN cana-616 158 7 πœ‚π‘‘ πœ‚π‘‘ ADP cana-616 158 8 βˆ’ βˆ’ PROPN cana-616 158 9 πœ‚0𝑒 πœ‚0𝑒 NOUN cana-616 158 10 βˆ’π‘˜π‘‘ βˆ’π‘˜π‘‘ VERB cana-616 158 11 ( ( PUNCT cana-616 158 12 25 25 NUM cana-616 158 13 ) ) PUNCT cana-616 158 14 where where SCONJ cana-616 158 15 πœ‚0 πœ‚0 NOUN cana-616 158 16 is be AUX cana-616 158 17 the the DET cana-616 158 18 initial initial ADJ cana-616 158 19 learning learning NOUN cana-616 158 20 rate rate NOUN cana-616 158 21 , , PUNCT cana-616 158 22 π‘˜ π‘˜ PRON cana-616 158 23 is be AUX cana-616 158 24 the the DET cana-616 158 25 decay decay NOUN cana-616 158 26 rate rate NOUN cana-616 158 27 , , PUNCT cana-616 158 28 and and CCONJ cana-616 158 29 𝑑 𝑑 PROPN cana-616 158 30 is be AUX cana-616 158 31 the the DET cana-616 158 32 iteration iteration NOUN cana-616 158 33 number number NOUN cana-616 158 34 . . PUNCT cana-616 159 1 this this PRON cana-616 159 2 helps help VERB cana-616 159 3 in in ADP cana-616 159 4 stabilizing stabilize VERB cana-616 159 5 learning learning NOUN cana-616 159 6 as as ADP cana-616 159 7 the the DET cana-616 159 8 iterations iteration NOUN cana-616 159 9 progress progress NOUN cana-616 159 10 . . PUNCT cana-616 160 1 cyclical cyclical ADJ cana-616 160 2 learning learning NOUN cana-616 160 3 rates rate NOUN cana-616 160 4 πœ‚π‘‘ πœ‚π‘‘ ADP cana-616 160 5 βˆ’ βˆ’ NOUN cana-616 160 6 πœ‚min πœ‚min NOUN cana-616 160 7 + + CCONJ cana-616 160 8 1 1 NUM cana-616 160 9 2 2 NUM cana-616 160 10 ( ( PUNCT cana-616 160 11 πœ‚max πœ‚max NOUN cana-616 160 12 βˆ’ βˆ’ NOUN cana-616 160 13 πœ‚min πœ‚min NOUN cana-616 160 14 ) ) PUNCT cana-616 160 15 ( ( PUNCT cana-616 160 16 1 1 X cana-616 160 17 + + CCONJ cana-616 160 18 cos⁑ cos⁑ X cana-616 160 19 ( ( PUNCT cana-616 160 20 𝑇mat 𝑇mat PROPN cana-616 160 21 𝑇max 𝑇max PROPN cana-616 160 22 πœ‹ πœ‹ NOUN cana-616 160 23 ) ) PUNCT cana-616 160 24 ) ) PUNCT cana-616 160 25 ( ( PUNCT cana-616 160 26 26 26 NUM cana-616 160 27 ) ) PUNCT cana-616 160 28 this this DET cana-616 160 29 strategy strategy NOUN cana-616 160 30 varies vary VERB cana-616 160 31 the the DET cana-616 160 32 learning learning NOUN cana-616 160 33 rate rate NOUN cana-616 160 34 cyclically cyclically ADV cana-616 160 35 between between ADP cana-616 160 36 πœ‚min πœ‚min NOUN cana-616 160 37 and and CCONJ cana-616 160 38 πœ‚max πœ‚max NOUN cana-616 160 39 , , PUNCT cana-616 160 40 where where SCONJ cana-616 160 41 𝑇cur 𝑇cur PROPN cana-616 160 42 is be AUX cana-616 160 43 the the DET cana-616 160 44 current current ADJ cana-616 160 45 epoch epoch NOUN cana-616 160 46 number number NOUN cana-616 160 47 and and CCONJ cana-616 160 48 𝑇max 𝑇max PROPN cana-616 160 49 is be AUX cana-616 160 50 the the DET cana-616 160 51 maximum maximum ADJ cana-616 160 52 number number NOUN cana-616 160 53 of of ADP cana-616 160 54 epochs epoch NOUN cana-616 160 55 . . PUNCT cana-616 161 1 evaluation evaluation NOUN cana-616 161 2 metrics metric NOUN cana-616 161 3 for for ADP cana-616 161 4 classification classification NOUN cana-616 161 5 specificity specificity NOUN cana-616 161 6 specificity specificity NOUN cana-616 161 7 = = SYM cana-616 161 8 𝑇𝑁 𝑇𝑁 ADJ cana-616 161 9 𝑇𝑁+𝐹𝑇 𝑇𝑁+𝐹𝑇 VERB cana-616 161 10 specificity specificity NOUN cana-616 161 11 measures measure VERB cana-616 161 12 the the DET cana-616 161 13 proportion proportion NOUN cana-616 161 14 of of ADP cana-616 161 15 actual actual ADJ cana-616 161 16 negatives negative NOUN cana-616 161 17 that that PRON cana-616 161 18 are be AUX cana-616 161 19 correctly correctly ADV cana-616 161 20 identified identify VERB cana-616 161 21 , , PUNCT cana-616 161 22 essential essential ADJ cana-616 161 23 for for ADP cana-616 161 24 medical medical ADJ cana-616 161 25 diagnostic diagnostic ADJ cana-616 161 26 tests test NOUN cana-616 161 27 . . PUNCT cana-616 162 1 balanced balanced ADJ cana-616 162 2 accuracy accuracy NOUN cana-616 162 3 balanced balanced ADJ cana-616 162 4 accuracy accuracy NOUN cana-616 162 5 = = SYM cana-616 162 6 sensitivity+specificity sensitivity+specificity PROPN cana-616 162 7 balanced balanced ADJ cana-616 162 8 accuracy accuracy NOUN cana-616 162 9 is be AUX cana-616 162 10 particularly particularly ADV cana-616 162 11 useful useful ADJ cana-616 162 12 when when SCONJ cana-616 162 13 dealing deal VERB cana-616 162 14 with with ADP cana-616 162 15 imbalanced imbalanced ADJ cana-616 162 16 datasets dataset NOUN cana-616 162 17 . . PUNCT cana-616 163 1 optimization optimization NOUN cana-616 163 2 for for ADP cana-616 163 3 sparse sparse ADJ cana-616 163 4 data data NOUN cana-616 163 5 elastic elastic ADJ cana-616 163 6 net net ADJ cana-616 163 7 regularization regularization NOUN cana-616 163 8 𝐽(πœƒ 𝐽(πœƒ NOUN cana-616 163 9 ) ) PUNCT cana-616 163 10 = = SYM cana-616 163 11 loss⁑(πœƒ loss⁑(πœƒ X cana-616 163 12 ) ) PUNCT cana-616 164 1 + + CCONJ cana-616 164 2 π‘Ÿπœ†βˆ‘ π‘Ÿπœ†βˆ‘ ADV cana-616 164 3 β€Š β€Š SPACE cana-616 164 4 𝑛 𝑛 DET cana-616 164 5 π‘—βˆ’1 π‘—βˆ’1 PROPN cana-616 164 6 |πœƒπ‘—| |πœƒπ‘—| NOUN cana-616 165 1 + + CCONJ cana-616 165 2 1βˆ’π‘Ÿ 1βˆ’π‘Ÿ NUM cana-616 165 3 2 2 NUM cana-616 165 4 πœ† πœ† PRON cana-616 165 5 βˆ‘ βˆ‘ DET cana-616 165 6 β€Š β€Š SPACE cana-616 165 7 𝑛 𝑛 DET cana-616 165 8 π‘—βˆ’1 π‘—βˆ’1 PROPN cana-616 165 9 πœƒπ‘— πœƒπ‘— VERB cana-616 165 10 2 2 NUM cana-616 165 11 ( ( PUNCT cana-616 165 12 27 27 NUM cana-616 165 13 ) ) PUNCT cana-616 165 14 where where SCONJ cana-616 165 15 π‘Ÿ π‘Ÿ PRON cana-616 165 16 is be AUX cana-616 165 17 the the DET cana-616 165 18 mixing mix VERB cana-616 165 19 parameter parameter NOUN cana-616 165 20 between between ADP cana-616 165 21 l1 l1 PROPN cana-616 165 22 and and CCONJ cana-616 165 23 l2 l2 NOUN cana-616 165 24 regularization regularization NOUN cana-616 165 25 , , PUNCT cana-616 165 26 providing provide VERB cana-616 165 27 a a DET cana-616 165 28 balance balance NOUN cana-616 165 29 that that PRON cana-616 165 30 encourages encourage VERB cana-616 165 31 model model NOUN cana-616 165 32 sparsity sparsity NOUN cana-616 165 33 while while SCONJ cana-616 165 34 retaining retain VERB cana-616 165 35 regularization regularization NOUN cana-616 165 36 benefits benefit NOUN cana-616 165 37 of of ADP cana-616 165 38 𝐿2 𝐿2 PROPN cana-616 165 39 . . PUNCT cana-616 166 1 these these PRON cana-616 166 2 enhance enhance VERB cana-616 166 3 the the DET cana-616 166 4 analytical analytical ADJ cana-616 166 5 depth depth NOUN cana-616 166 6 of of ADP cana-616 166 7 optimization optimization NOUN cana-616 166 8 techniques technique NOUN cana-616 166 9 and and CCONJ cana-616 166 10 evaluation evaluation NOUN cana-616 166 11 strategies strategy NOUN cana-616 166 12 , , PUNCT cana-616 166 13 essential essential ADJ cana-616 166 14 for for ADP cana-616 166 15 tailoring tailor VERB cana-616 166 16 machine machine NOUN cana-616 166 17 learning learning NOUN cana-616 166 18 models model NOUN cana-616 166 19 to to ADP cana-616 166 20 specific specific ADJ cana-616 166 21 challenges challenge NOUN cana-616 166 22 such such ADJ cana-616 166 23 as as ADP cana-616 166 24 high high ADJ cana-616 166 25 dimensional dimensional ADJ cana-616 166 26 and and CCONJ cana-616 166 27 noisy noisy ADJ cana-616 166 28 datasets dataset NOUN cana-616 166 29 like like ADP cana-616 166 30 those those PRON cana-616 166 31 encountered encounter VERB cana-616 166 32 in in ADP cana-616 166 33 image image NOUN cana-616 166 34 - - PUNCT cana-616 166 35 based base VERB cana-616 166 36 disease disease NOUN cana-616 166 37 classification classification NOUN cana-616 166 38 . . PUNCT cana-616 167 1 2 2 X cana-616 167 2 . . X cana-616 167 3 integrating integrate VERB cana-616 167 4 bayesian bayesian NOUN cana-616 167 5 optimization optimization NOUN cana-616 167 6 : : PUNCT cana-616 167 7 β€’ β€’ ADP cana-616 167 8 bayesian bayesian NOUN cana-616 167 9 posterior posterior ADJ cana-616 167 10 probability probability NOUN cana-616 167 11 updates update NOUN cana-616 167 12 and and CCONJ cana-616 167 13 gaussian gaussian ADJ cana-616 167 14 process process NOUN cana-616 167 15 ( ( PUNCT cana-616 167 16 gp gp NOUN cana-616 167 17 ) ) PUNCT cana-616 167 18 regressionprovide regressionprovide NOUN cana-616 167 19 a a DET cana-616 167 20 probabilistic probabilistic ADJ cana-616 167 21 belief belief NOUN cana-616 167 22 in in ADP cana-616 167 23 model model NOUN cana-616 167 24 performance performance NOUN cana-616 167 25 across across ADP cana-616 167 26 the the DET cana-616 167 27 hyperparameter hyperparameter NOUN cana-616 167 28 space space NOUN cana-616 167 29 . . PUNCT cana-616 168 1 using use VERB cana-616 168 2 acquisition acquisition NOUN cana-616 168 3 communications communication NOUN cana-616 168 4 on on ADP cana-616 168 5 applied apply VERB cana-616 168 6 nonlinear nonlinear ADJ cana-616 168 7 analysis analysis NOUN cana-616 168 8 issn issn NOUN cana-616 168 9 : : PUNCT cana-616 168 10 1074 1074 NUM cana-616 168 11 - - PUNCT cana-616 168 12 133x 133x NUM cana-616 168 13 vol vol NOUN cana-616 168 14 31 31 NUM cana-616 168 15 no no NOUN cana-616 168 16 . . PUNCT cana-616 169 1 2s 2s NUM cana-616 169 2 ( ( PUNCT cana-616 169 3 2024 2024 NUM cana-616 169 4 ) ) PUNCT cana-616 169 5 129 129 NUM cana-616 169 6 https://internationalpubls.com https://internationalpubls.com X cana-616 169 7 functions function NOUN cana-616 169 8 like like ADP cana-616 169 9 expected expect VERB cana-616 169 10 improvement improvement NOUN cana-616 169 11 ( ( PUNCT cana-616 169 12 equation equation NOUN cana-616 169 13 8) 8) NUM cana-616 169 14 , , PUNCT cana-616 169 15 we we PRON cana-616 169 16 can can AUX cana-616 169 17 efficiently efficiently ADV cana-616 169 18 explore explore VERB cana-616 169 19 and and CCONJ cana-616 169 20 exploit exploit VERB cana-616 169 21 the the DET cana-616 169 22 space space NOUN cana-616 169 23 to to PART cana-616 169 24 find find VERB cana-616 169 25 optimal optimal ADJ cana-616 169 26 settings setting NOUN cana-616 169 27 faster fast ADV cana-616 169 28 and and CCONJ cana-616 169 29 more more ADV cana-616 169 30 effectively effectively ADV cana-616 169 31 than than ADP cana-616 169 32 grid grid ADJ cana-616 169 33 or or CCONJ cana-616 169 34 random random ADJ cana-616 169 35 search search NOUN cana-616 169 36 methods method NOUN cana-616 169 37 . . PUNCT cana-616 170 1 β€’ β€’ NUM cana-616 170 2 knowledge knowledge NOUN cana-616 170 3 gradient gradient NOUN cana-616 170 4 and and CCONJ cana-616 170 5 predictive predictive ADJ cana-616 170 6 entropy entropy NOUN cana-616 170 7 search search NOUN cana-616 170 8 help help NOUN cana-616 170 9 in in ADP cana-616 170 10 selecting select VERB cana-616 170 11 the the DET cana-616 170 12 next next ADJ cana-616 170 13 hyperparameters hyperparameter NOUN cana-616 170 14 to to PART cana-616 170 15 evaluate evaluate VERB cana-616 170 16 by by ADP cana-616 170 17 balancing balance VERB cana-616 170 18 the the DET cana-616 170 19 trade trade NOUN cana-616 170 20 - - PUNCT cana-616 170 21 off off NOUN cana-616 170 22 between between ADP cana-616 170 23 exploration exploration NOUN cana-616 170 24 of of ADP cana-616 170 25 underexplored underexplored ADJ cana-616 170 26 areas area NOUN cana-616 170 27 and and CCONJ cana-616 170 28 exploitation exploitation NOUN cana-616 170 29 of of ADP cana-616 170 30 known know VERB cana-616 170 31 good good ADJ cana-616 170 32 areas area NOUN cana-616 170 33 . . PUNCT cana-616 171 1 advanced advanced ADJ cana-616 171 2 optimization optimization NOUN cana-616 171 3 techniques technique NOUN cana-616 171 4 improving improve VERB cana-616 171 5 the the DET cana-616 171 6 rf rf NOUN cana-616 171 7 involves involve VERB cana-616 171 8 not not PART cana-616 171 9 only only ADV cana-616 171 10 selecting select VERB cana-616 171 11 the the DET cana-616 171 12 best good ADJ cana-616 171 13 hyperparameters hyperparameter NOUN cana-616 171 14 but but CCONJ cana-616 171 15 also also ADV cana-616 171 16 optimizing optimize VERB cana-616 171 17 the the DET cana-616 171 18 learning learning NOUN cana-616 171 19 process process NOUN cana-616 171 20 during during ADP cana-616 171 21 the the DET cana-616 171 22 construction construction NOUN cana-616 171 23 of of ADP cana-616 171 24 the the DET cana-616 171 25 trees tree NOUN cana-616 171 26 . . PUNCT cana-616 172 1 3 3 X cana-616 172 2 . . X cana-616 172 3 learning learn VERB cana-616 172 4 rate rate NOUN cana-616 172 5 and and CCONJ cana-616 172 6 optimization optimization NOUN cana-616 172 7 adjustments adjustment NOUN cana-616 172 8 : : PUNCT cana-616 172 9 β€’ β€’ NOUN cana-616 172 10 exponential exponential ADJ cana-616 172 11 and and CCONJ cana-616 172 12 cyclical cyclical ADJ cana-616 172 13 learning learning NOUN cana-616 172 14 rates rate NOUN cana-616 172 15 can can AUX cana-616 172 16 be be AUX cana-616 172 17 adapted adapt VERB cana-616 172 18 for for ADP cana-616 172 19 use use NOUN cana-616 172 20 in in ADP cana-616 172 21 the the DET cana-616 172 22 rf rf ADJ cana-616 172 23 context context NOUN cana-616 172 24 by by ADP cana-616 172 25 adjusting adjust VERB cana-616 172 26 them they PRON cana-616 172 27 during during ADP cana-616 172 28 the the DET cana-616 172 29 bootstrapping bootstrapping NOUN cana-616 172 30 of of ADP cana-616 172 31 samples sample NOUN cana-616 172 32 used use VERB cana-616 172 33 to to PART cana-616 172 34 build build VERB cana-616 172 35 individual individual ADJ cana-616 172 36 trees tree NOUN cana-616 172 37 , , PUNCT cana-616 172 38 thereby thereby ADV cana-616 172 39 affecting affect VERB cana-616 172 40 how how SCONJ cana-616 172 41 each each DET cana-616 172 42 tree tree NOUN cana-616 172 43 learns learn VERB cana-616 172 44 from from ADP cana-616 172 45 its its PRON cana-616 172 46 subset subset NOUN cana-616 172 47 of of ADP cana-616 172 48 the the DET cana-616 172 49 data datum NOUN cana-616 172 50 . . PUNCT cana-616 173 1 β€’ β€’ NUM cana-616 173 2 adam adam PROPN cana-616 173 3 optimization optimization NOUN cana-616 173 4 and and CCONJ cana-616 173 5 momentum momentum NOUN cana-616 173 6 - - PUNCT cana-616 173 7 based base VERB cana-616 173 8 updates update NOUN cana-616 173 9 might might AUX cana-616 173 10 influence influence VERB cana-616 173 11 the the DET cana-616 173 12 feature feature NOUN cana-616 173 13 selection selection NOUN cana-616 173 14 phase phase NOUN cana-616 173 15 in in ADP cana-616 173 16 tree tree NOUN cana-616 173 17 construction construction NOUN cana-616 173 18 , , PUNCT cana-616 173 19 particularly particularly ADV cana-616 173 20 when when SCONJ cana-616 173 21 features feature NOUN cana-616 173 22 are be AUX cana-616 173 23 high high ADV cana-616 173 24 - - PUNCT cana-616 173 25 dimensional dimensional ADJ cana-616 173 26 and and CCONJ cana-616 173 27 interactions interaction NOUN cana-616 173 28 are be AUX cana-616 173 29 complex complex ADJ cana-616 173 30 . . PUNCT cana-616 174 1 regularization regularization NOUN cana-616 174 2 techniques technique NOUN cana-616 174 3 to to PART cana-616 174 4 prevent prevent VERB cana-616 174 5 overfitting overfitting NOUN cana-616 174 6 , , PUNCT cana-616 174 7 especially especially ADV cana-616 174 8 when when SCONJ cana-616 174 9 rf rf NOUN cana-616 174 10 is be AUX cana-616 174 11 applied apply VERB cana-616 174 12 to to ADP cana-616 174 13 high high ADJ cana-616 174 14 - - PUNCT cana-616 174 15 dimensional dimensional ADJ cana-616 174 16 image image NOUN cana-616 174 17 data datum NOUN cana-616 174 18 , , PUNCT cana-616 174 19 regularization regularization NOUN cana-616 174 20 techniques technique NOUN cana-616 174 21 can can AUX cana-616 174 22 be be AUX cana-616 174 23 essential essential ADJ cana-616 174 24 . . PUNCT cana-616 175 1 4 4 X cana-616 175 2 . . X cana-616 175 3 regularization regularization NOUN cana-616 175 4 integration integration NOUN cana-616 175 5 : : PUNCT cana-616 175 6 β€’ β€’ NUM cana-616 175 7 l2 l2 NOUN cana-616 175 8 and and CCONJ cana-616 175 9 l1 l1 PROPN cana-616 175 10 regularizations regularization NOUN cana-616 175 11 can can AUX cana-616 175 12 be be AUX cana-616 175 13 applied apply VERB cana-616 175 14 during during ADP cana-616 175 15 the the DET cana-616 175 16 tree tree NOUN cana-616 175 17 construction construction NOUN cana-616 175 18 by by ADP cana-616 175 19 penalizing penalize VERB cana-616 175 20 the the DET cana-616 175 21 growth growth NOUN cana-616 175 22 of of ADP cana-616 175 23 trees tree NOUN cana-616 175 24 with with ADP cana-616 175 25 overly overly ADV cana-616 175 26 complex complex ADJ cana-616 175 27 structures structure NOUN cana-616 175 28 or or CCONJ cana-616 175 29 by by ADP cana-616 175 30 encouraging encourage VERB cana-616 175 31 sparsity sparsity NOUN cana-616 175 32 in in ADP cana-616 175 33 the the DET cana-616 175 34 features feature NOUN cana-616 175 35 used use VERB cana-616 175 36 by by ADP cana-616 175 37 individual individual ADJ cana-616 175 38 trees tree NOUN cana-616 175 39 . . PUNCT cana-616 176 1 β€’ β€’ NUM cana-616 176 2 elastic elastic ADJ cana-616 176 3 net net ADJ cana-616 176 4 regularization regularization NOUN cana-616 176 5 combines combine VERB cana-616 176 6 these these DET cana-616 176 7 approaches approach NOUN cana-616 176 8 , , PUNCT cana-616 176 9 potentially potentially ADV cana-616 176 10 useful useful ADJ cana-616 176 11 in in ADP cana-616 176 12 scenarios scenario NOUN cana-616 176 13 where where SCONJ cana-616 176 14 both both PRON cana-616 176 15 feature feature NOUN cana-616 176 16 selection selection NOUN cana-616 176 17 and and CCONJ cana-616 176 18 model model NOUN cana-616 176 19 complexity complexity NOUN cana-616 176 20 control control NOUN cana-616 176 21 are be AUX cana-616 176 22 crucial crucial ADJ cana-616 176 23 . . PUNCT cana-616 177 1 performance performance NOUN cana-616 177 2 evaluation evaluation NOUN cana-616 177 3 and and CCONJ cana-616 177 4 model model NOUN cana-616 177 5 complexity complexity NOUN cana-616 177 6 accurately accurately ADV cana-616 177 7 measuring measure VERB cana-616 177 8 the the DET cana-616 177 9 performance performance NOUN cana-616 177 10 of of ADP cana-616 177 11 the the DET cana-616 177 12 rf rf NOUN cana-616 177 13 model model NOUN cana-616 177 14 and and CCONJ cana-616 177 15 understanding understand VERB cana-616 177 16 the the DET cana-616 177 17 error error NOUN cana-616 177 18 dynamics dynamic NOUN cana-616 177 19 are be AUX cana-616 177 20 crucial crucial ADJ cana-616 177 21 for for ADP cana-616 177 22 ensuring ensure VERB cana-616 177 23 the the DET cana-616 177 24 model model NOUN cana-616 177 25 is be AUX cana-616 177 26 both both CCONJ cana-616 177 27 accurate accurate ADJ cana-616 177 28 and and CCONJ cana-616 177 29 generalizable generalizable ADJ cana-616 177 30 . . PUNCT cana-616 178 1 5 5 NUM cana-616 178 2 . . X cana-616 178 3 error error NOUN cana-616 178 4 and and CCONJ cana-616 178 5 performance performance NOUN cana-616 178 6 metrics metric NOUN cana-616 178 7 : : PUNCT cana-616 178 8 β€’ β€’ NUM cana-616 178 9 bias bias NOUN cana-616 178 10 - - PUNCT cana-616 178 11 variance variance NOUN cana-616 178 12 decomposition decomposition NOUN cana-616 178 13 provides provide VERB cana-616 178 14 a a DET cana-616 178 15 framework framework NOUN cana-616 178 16 to to PART cana-616 178 17 understand understand VERB cana-616 178 18 how how SCONJ cana-616 178 19 different different ADJ cana-616 178 20 sources source NOUN cana-616 178 21 of of ADP cana-616 178 22 error error NOUN cana-616 178 23 contribute contribute VERB cana-616 178 24 to to ADP cana-616 178 25 the the DET cana-616 178 26 overall overall ADJ cana-616 178 27 error error NOUN cana-616 178 28 , , PUNCT cana-616 178 29 guiding guide VERB cana-616 178 30 further further ADJ cana-616 178 31 tuning tuning NOUN cana-616 178 32 and and CCONJ cana-616 178 33 adjustments adjustment NOUN cana-616 178 34 . . PUNCT cana-616 179 1 β€’ β€’ NUM cana-616 179 2 metrics metric NOUN cana-616 179 3 like like ADP cana-616 179 4 precision precision NOUN cana-616 179 5 , , PUNCT cana-616 179 6 recall recall NOUN cana-616 179 7 , , PUNCT cana-616 179 8 f1 f1 NOUN cana-616 179 9 score score NOUN cana-616 179 10 , , PUNCT cana-616 179 11 specificity specificity NOUN cana-616 179 12 , , PUNCT cana-616 179 13 and and CCONJ cana-616 179 14 balanced balanced ADJ cana-616 179 15 accuracy accuracy NOUN cana-616 179 16 are be AUX cana-616 179 17 vital vital ADJ cana-616 179 18 for for ADP cana-616 179 19 evaluating evaluate VERB cana-616 179 20 the the DET cana-616 179 21 performance performance NOUN cana-616 179 22 of of ADP cana-616 179 23 the the DET cana-616 179 24 rf rf NOUN cana-616 179 25 classifier classifier NOUN cana-616 179 26 , , PUNCT cana-616 179 27 particularly particularly ADV cana-616 179 28 in in ADP cana-616 179 29 medical medical ADJ cana-616 179 30 imaging imaging NOUN cana-616 179 31 contexts context NOUN cana-616 179 32 where where SCONJ cana-616 179 33 false false ADJ cana-616 179 34 negatives negative NOUN cana-616 179 35 or or CCONJ cana-616 179 36 positives positive NOUN cana-616 179 37 have have VERB cana-616 179 38 significant significant ADJ cana-616 179 39 consequences consequence NOUN cana-616 179 40 . . PUNCT cana-616 180 1 communications communication NOUN cana-616 180 2 on on ADP cana-616 180 3 applied apply VERB cana-616 180 4 nonlinear nonlinear ADJ cana-616 180 5 analysis analysis NOUN cana-616 180 6 issn issn NOUN cana-616 180 7 : : PUNCT cana-616 180 8 1074 1074 NUM cana-616 180 9 - - PUNCT cana-616 180 10 133x 133x NUM cana-616 180 11 vol vol NOUN cana-616 180 12 31 31 NUM cana-616 180 13 no no NOUN cana-616 180 14 . . PUNCT cana-616 181 1 2s 2s NUM cana-616 181 2 ( ( PUNCT cana-616 181 3 2024 2024 NUM cana-616 181 4 ) ) PUNCT cana-616 181 5 130 130 NUM cana-616 181 6 https://internationalpubls.com https://internationalpubls.com X cana-616 181 7 data datum NOUN cana-616 181 8 preprocessing preprocessing NOUN cana-616 181 9 involves involve VERB cana-616 181 10 several several ADJ cana-616 181 11 sub sub NOUN cana-616 181 12 - - NOUN cana-616 181 13 steps step NOUN cana-616 181 14 : : PUNCT cana-616 181 15 cleaning clean VERB cana-616 181 16 : : PUNCT cana-616 181 17 for for ADP cana-616 181 18 this this PRON cana-616 181 19 , , PUNCT cana-616 181 20 the the DET cana-616 181 21 strategy strategy NOUN cana-616 181 22 employed employ VERB cana-616 181 23 includes include VERB cana-616 181 24 the the DET cana-616 181 25 treatment treatment NOUN cana-616 181 26 of of ADP cana-616 181 27 missing miss VERB cana-616 181 28 values value NOUN cana-616 181 29 that that SCONJ cana-616 181 30 in in ADP cana-616 181 31 some some DET cana-616 181 32 cases case NOUN cana-616 181 33 could could AUX cana-616 181 34 be be AUX cana-616 181 35 imputed impute VERB cana-616 181 36 , , PUNCT cana-616 181 37 and and CCONJ cana-616 181 38 in in ADP cana-616 181 39 others other NOUN cana-616 181 40 just just ADV cana-616 181 41 removed remove VERB cana-616 181 42 considering consider VERB cana-616 181 43 their their PRON cana-616 181 44 volume volume NOUN cana-616 181 45 and and CCONJ cana-616 181 46 impact impact NOUN cana-616 181 47 on on ADP cana-616 181 48 the the DET cana-616 181 49 dataset dataset NOUN cana-616 181 50 . . PUNCT cana-616 182 1 either either CCONJ cana-616 182 2 than than ADP cana-616 182 3 in in ADP cana-616 182 4 the the DET cana-616 182 5 normalizing normalizing ADJ cana-616 182 6 approaches approach NOUN cana-616 182 7 , , PUNCT cana-616 182 8 outliers outlier NOUN cana-616 182 9 are be AUX cana-616 182 10 controlled control VERB cana-616 182 11 by by ADP cana-616 182 12 specialized specialized ADJ cana-616 182 13 techniques technique NOUN cana-616 182 14 or or CCONJ cana-616 182 15 thresholds threshold NOUN cana-616 182 16 that that PRON cana-616 182 17 create create VERB cana-616 182 18 a a DET cana-616 182 19 normal normal ADJ cana-616 182 20 data datum NOUN cana-616 182 21 range range NOUN cana-616 182 22 . . PUNCT cana-616 183 1 transformation transformation NOUN cana-616 183 2 : : PUNCT cana-616 183 3 applying apply VERB cana-616 183 4 normalization normalization NOUN cana-616 183 5 or or CCONJ cana-616 183 6 standardization standardization NOUN cana-616 183 7 is be AUX cana-616 183 8 crucial crucial ADJ cana-616 183 9 when when SCONJ cana-616 183 10 dealing deal VERB cana-616 183 11 with with ADP cana-616 183 12 features feature NOUN cana-616 183 13 that that PRON cana-616 183 14 vary vary VERB cana-616 183 15 in in ADP cana-616 183 16 scale scale NOUN cana-616 183 17 and and CCONJ cana-616 183 18 distribution distribution NOUN cana-616 183 19 , , PUNCT cana-616 183 20 as as SCONJ cana-616 183 21 this this PRON cana-616 183 22 can can AUX cana-616 183 23 significantly significantly ADV cana-616 183 24 impact impact VERB cana-616 183 25 the the DET cana-616 183 26 performance performance NOUN cana-616 183 27 of of ADP cana-616 183 28 many many ADJ cana-616 183 29 machine machine NOUN cana-616 183 30 learning learn VERB cana-616 183 31 algorithms algorithm NOUN cana-616 183 32 . . PUNCT cana-616 184 1 β€’ β€’ NUM cana-616 184 2 feature feature NOUN cana-616 184 3 engineering engineering NOUN cana-616 184 4 : : PUNCT cana-616 184 5 this this PRON cana-616 184 6 is be AUX cana-616 184 7 the the DET cana-616 184 8 next next ADJ cana-616 184 9 step step NOUN cana-616 184 10 after after ADP cana-616 184 11 the the DET cana-616 184 12 creation creation NOUN cana-616 184 13 of of ADP cana-616 184 14 new new ADJ cana-616 184 15 features feature NOUN cana-616 184 16 by by ADP cana-616 184 17 using use VERB cana-616 184 18 already already ADV cana-616 184 19 available available ADJ cana-616 184 20 in in ADP cana-616 184 21 training training NOUN cana-616 184 22 data datum NOUN cana-616 184 23 . . PUNCT cana-616 185 1 new new ADJ cana-616 185 2 features feature NOUN cana-616 185 3 bring bring VERB cana-616 185 4 a a DET cana-616 185 5 higher high ADJ cana-616 185 6 predictive predictive ADJ cana-616 185 7 power power NOUN cana-616 185 8 of of ADP cana-616 185 9 model model NOUN cana-616 185 10 . . PUNCT cana-616 186 1 for for ADP cana-616 186 2 example example NOUN cana-616 186 3 , , PUNCT cana-616 186 4 joining join VERB cana-616 186 5 elements element NOUN cana-616 186 6 to to PART cana-616 186 7 form form VERB cana-616 186 8 a a DET cana-616 186 9 class class NOUN cana-616 186 10 of of ADP cana-616 186 11 disease disease NOUN cana-616 186 12 measurements measurement NOUN cana-616 186 13 that that PRON cana-616 186 14 are be AUX cana-616 186 15 worsening worsen VERB cana-616 186 16 over over ADP cana-616 186 17 time time NOUN cana-616 186 18 or or CCONJ cana-616 186 19 creating create VERB cana-616 186 20 time time NOUN cana-616 186 21 - - PUNCT cana-616 186 22 based base VERB cana-616 186 23 features feature NOUN cana-616 186 24 to to PART cana-616 186 25 take take VERB cana-616 186 26 into into ADP cana-616 186 27 account account NOUN cana-616 186 28 seasonal seasonal ADJ cana-616 186 29 effects effect NOUN cana-616 186 30 can can AUX cana-616 186 31 be be AUX cana-616 186 32 also also ADV cana-616 186 33 helpful helpful ADJ cana-616 186 34 . . PUNCT cana-616 187 1 exploratory exploratory ADJ cana-616 187 2 data datum NOUN cana-616 187 3 analysis analysis NOUN cana-616 187 4 ( ( PUNCT cana-616 187 5 eda eda PROPN cana-616 187 6 ) ) PUNCT cana-616 187 7 exploratory exploratory ADJ cana-616 187 8 data datum NOUN cana-616 187 9 analysis analysis NOUN cana-616 187 10 should should AUX cana-616 187 11 be be AUX cana-616 187 12 applied apply VERB cana-616 187 13 for for ADP cana-616 187 14 the the DET cana-616 187 15 purpose purpose NOUN cana-616 187 16 of of ADP cana-616 187 17 visualizing visualize VERB cana-616 187 18 starting start VERB cana-616 187 19 the the DET cana-616 187 20 data datum NOUN cana-616 187 21 exploration exploration NOUN cana-616 187 22 and and CCONJ cana-616 187 23 modeling modeling NOUN cana-616 187 24 process process NOUN cana-616 187 25 . . PUNCT cana-616 188 1 through through ADP cana-616 188 2 visualization visualization NOUN cana-616 188 3 techniques technique NOUN cana-616 188 4 like like ADP cana-616 188 5 histogram histogram NOUN cana-616 188 6 , , PUNCT cana-616 188 7 scatterplot scatterplot NOUN cana-616 188 8 , , PUNCT cana-616 188 9 and and CCONJ cana-616 188 10 box box NOUN cana-616 188 11 plots plot VERB cana-616 188 12 one one NUM cana-616 188 13 grasp grasp VERB cana-616 188 14 the the DET cana-616 188 15 distribution distribution NOUN cana-616 188 16 and and CCONJ cana-616 188 17 understand understand VERB cana-616 188 18 the the DET cana-616 188 19 patterns pattern NOUN cana-616 188 20 which which PRON cana-616 188 21 could could AUX cana-616 188 22 lead lead VERB cana-616 188 23 to to ADP cana-616 188 24 the the DET cana-616 188 25 enquiry enquiry NOUN cana-616 188 26 or or CCONJ cana-616 188 27 investigation investigation NOUN cana-616 188 28 of of ADP cana-616 188 29 outliers outlier NOUN cana-616 188 30 . . PUNCT cana-616 189 1 correlation correlation NOUN cana-616 189 2 tables table NOUN cana-616 189 3 and and CCONJ cana-616 189 4 severer severe ADJ cana-616 189 5 test test NOUN cana-616 189 6 principles principle NOUN cana-616 189 7 are be AUX cana-616 189 8 being be AUX cana-616 189 9 acquired acquire VERB cana-616 189 10 to to PART cana-616 189 11 attain attain VERB cana-616 189 12 insight insight NOUN cana-616 189 13 into into ADP cana-616 189 14 relationships relationship NOUN cana-616 189 15 among among ADP cana-616 189 16 variables variable NOUN cana-616 189 17 as as ADV cana-616 189 18 well well ADV cana-616 189 19 as as ADP cana-616 189 20 relevant relevant ADJ cana-616 189 21 features feature NOUN cana-616 189 22 for for ADP cana-616 189 23 model model NOUN cana-616 189 24 . . PUNCT cana-616 190 1 the the DET cana-616 190 2 dataset dataset NOUN cana-616 190 3 consists consist VERB cana-616 190 4 of of ADP cana-616 190 5 several several ADJ cana-616 190 6 fields field NOUN cana-616 190 7 that that PRON cana-616 190 8 describe describe VERB cana-616 190 9 the the DET cana-616 190 10 livestock livestock NOUN cana-616 190 11 condition condition NOUN cana-616 190 12 , , PUNCT cana-616 190 13 whether whether SCONJ cana-616 190 14 lumpy lumpy ADJ cana-616 190 15 skin skin NOUN cana-616 190 16 disease disease NOUN cana-616 190 17 ( ( PUNCT cana-616 190 18 lsd lsd NOUN cana-616 190 19 ) ) PUNCT cana-616 190 20 is be AUX cana-616 190 21 present present ADJ cana-616 190 22 , , PUNCT cana-616 190 23 and and CCONJ cana-616 190 24 it it PRON cana-616 190 25 also also ADV cana-616 190 26 includes include VERB cana-616 190 27 climatic climatic ADJ cana-616 190 28 and and CCONJ cana-616 190 29 environmental environmental ADJ cana-616 190 30 conditions condition NOUN cana-616 190 31 that that SCONJ cana-616 190 32 livestock livestock NOUN cana-616 190 33 populations population NOUN cana-616 190 34 may may AUX cana-616 190 35 face face VERB cana-616 190 36 , , PUNCT cana-616 190 37 as as ADV cana-616 190 38 well well ADV cana-616 190 39 . . PUNCT cana-616 191 1 here here ADV cana-616 191 2 's be AUX cana-616 191 3 a a DET cana-616 191 4 brief brief ADJ cana-616 191 5 overview overview NOUN cana-616 191 6 of of ADP cana-616 191 7 the the DET cana-616 191 8 types type NOUN cana-616 191 9 of of ADP cana-616 191 10 data datum NOUN cana-616 191 11 included include VERB cana-616 191 12 and and CCONJ cana-616 191 13 their their PRON cana-616 191 14 descriptions description NOUN cana-616 191 15 : : PUNCT cana-616 191 16 here here ADV cana-616 191 17 's be AUX cana-616 191 18 a a DET cana-616 191 19 brief brief ADJ cana-616 191 20 overview overview NOUN cana-616 191 21 of of ADP cana-616 191 22 the the DET cana-616 191 23 types type NOUN cana-616 191 24 of of ADP cana-616 191 25 data datum NOUN cana-616 191 26 included include VERB cana-616 191 27 and and CCONJ cana-616 191 28 their their PRON cana-616 191 29 descriptions description NOUN cana-616 191 30 : : PUNCT cana-616 191 31 geographic geographic ADJ cana-616 191 32 coordinates coordinate NOUN cana-616 191 33 ( ( PUNCT cana-616 191 34 x x X cana-616 191 35 , , PUNCT cana-616 191 36 y y PROPN cana-616 191 37 ): ): PUNCT cana-616 191 38 longitude longitude NOUN cana-616 191 39 and and CCONJ cana-616 191 40 latitude latitude NOUN cana-616 191 41 . . PUNCT cana-616 192 1 β€’ β€’ NUM cana-616 192 2 region region NOUN cana-616 192 3 and and CCONJ cana-616 192 4 country country NOUN cana-616 192 5 : : PUNCT cana-616 192 6 geographic geographic ADJ cana-616 192 7 descriptors descriptor NOUN cana-616 192 8 . . PUNCT cana-616 193 1 β€’ β€’ NOUN cana-616 193 2 reporting reporting NOUN cana-616 193 3 date date NOUN cana-616 193 4 ( ( PUNCT cana-616 193 5 reporting report VERB cana-616 193 6 date date NOUN cana-616 193 7 ): ): PUNCT cana-616 193 8 date date NOUN cana-616 193 9 of of ADP cana-616 193 10 disease disease NOUN cana-616 193 11 report report NOUN cana-616 193 12 . . PUNCT cana-616 194 1 β€’ β€’ NUM cana-616 194 2 climatic climatic ADJ cana-616 194 3 variables variable NOUN cana-616 194 4 : : PUNCT cana-616 194 5 includes include VERB cana-616 194 6 cloud cloud NOUN cana-616 194 7 cover cover NOUN cana-616 194 8 ( ( PUNCT cana-616 194 9 cld cld NOUN cana-616 194 10 ) ) PUNCT cana-616 194 11 , , PUNCT cana-616 194 12 diurnal diurnal ADJ cana-616 194 13 temperature temperature NOUN cana-616 194 14 range range NOUN cana-616 194 15 ( ( PUNCT cana-616 194 16 dtr dtr NOUN cana-616 194 17 ) ) PUNCT cana-616 194 18 , , PUNCT cana-616 194 19 frost frost NOUN cana-616 194 20 days day NOUN cana-616 194 21 ( ( PUNCT cana-616 194 22 frs frs PROPN cana-616 194 23 ) ) PUNCT cana-616 194 24 , , PUNCT cana-616 194 25 potential potential ADJ cana-616 194 26 evapotranspiration evapotranspiration NOUN cana-616 194 27 ( ( PUNCT cana-616 194 28 pet pet NOUN cana-616 194 29 ) ) PUNCT cana-616 194 30 , , PUNCT cana-616 194 31 precipitation precipitation NOUN cana-616 194 32 ( ( PUNCT cana-616 194 33 pre pre ADJ cana-616 194 34 ) ) PUNCT cana-616 194 35 , , PUNCT cana-616 194 36 minimum minimum ADJ cana-616 194 37 temperature temperature NOUN cana-616 194 38 ( ( PUNCT cana-616 194 39 tmn tmn NOUN cana-616 194 40 ) ) PUNCT cana-616 194 41 , , PUNCT cana-616 194 42 mean mean VERB cana-616 194 43 temperature temperature NOUN cana-616 194 44 ( ( PUNCT cana-616 194 45 tmp tmp NOUN cana-616 194 46 ) ) PUNCT cana-616 194 47 , , PUNCT cana-616 194 48 maximum maximum ADJ cana-616 194 49 temperature temperature NOUN cana-616 194 50 ( ( PUNCT cana-616 194 51 tmx tmx NOUN cana-616 194 52 ) ) PUNCT cana-616 194 53 , , PUNCT cana-616 194 54 vapor vapor NOUN cana-616 194 55 pressure pressure NOUN cana-616 194 56 ( ( PUNCT cana-616 194 57 vap vap NOUN cana-616 194 58 ) ) PUNCT cana-616 194 59 , , PUNCT cana-616 194 60 and and CCONJ cana-616 194 61 wet wet ADJ cana-616 194 62 day day NOUN cana-616 194 63 frequency frequency NOUN cana-616 194 64 ( ( PUNCT cana-616 194 65 wet wet NOUN cana-616 194 66 ) ) PUNCT cana-616 194 67 . . PUNCT cana-616 195 1 β€’ β€’ NUM cana-616 195 2 elevation elevation NOUN cana-616 195 3 and and CCONJ cana-616 195 4 dominant dominant ADJ cana-616 195 5 land land NOUN cana-616 195 6 cover cover NOUN cana-616 195 7 : : PUNCT cana-616 195 8 environmental environmental ADJ cana-616 195 9 descriptors descriptor NOUN cana-616 195 10 . . PUNCT cana-616 196 1 β€’ β€’ NUM cana-616 196 2 human human ADJ cana-616 196 3 and and CCONJ cana-616 196 4 cattle cattle NOUN cana-616 196 5 density density NOUN cana-616 196 6 : : PUNCT cana-616 196 7 ( ( PUNCT cana-616 196 8 x5_ct_2010_da x5_ct_2010_da NOUN cana-616 196 9 and and CCONJ cana-616 196 10 x5_bf_2010_da x5_bf_2010_da X cana-616 196 11 respectively respectively ADV cana-616 196 12 ) ) PUNCT cana-616 196 13 . . PUNCT cana-616 197 1 β€’ β€’ NUM cana-616 197 2 lumpy lumpy ADJ cana-616 197 3 skin skin NOUN cana-616 197 4 disease disease NOUN cana-616 197 5 presence presence NOUN cana-616 197 6 ( ( PUNCT cana-616 197 7 lumpy lumpy NOUN cana-616 197 8 ): ): PUNCT cana-616 197 9 binary binary ADJ cana-616 197 10 indicator indicator NOUN cana-616 197 11 ( ( PUNCT cana-616 197 12 0 0 X cana-616 197 13 = = SYM cana-616 197 14 no no NOUN cana-616 197 15 , , PUNCT cana-616 197 16 1 1 NUM cana-616 197 17 = = SYM cana-616 197 18 yes yes NOUN cana-616 197 19 ) ) PUNCT cana-616 197 20 . . PUNCT cana-616 198 1 model model NOUN cana-616 198 2 selection selection NOUN cana-616 198 3 selecting select VERB cana-616 198 4 the the DET cana-616 198 5 appropriate appropriate ADJ cana-616 198 6 machine machine NOUN cana-616 198 7 learning learn VERB cana-616 198 8 algorithm algorithm NOUN cana-616 198 9 is be AUX cana-616 198 10 critical critical ADJ cana-616 198 11 to to ADP cana-616 198 12 the the DET cana-616 198 13 research research NOUN cana-616 198 14 's 's PART cana-616 198 15 success success NOUN cana-616 198 16 . . PUNCT cana-616 199 1 for for ADP cana-616 199 2 a a DET cana-616 199 3 classification classification NOUN cana-616 199 4 problem problem NOUN cana-616 199 5 like like ADP cana-616 199 6 lumpy lumpy ADJ cana-616 199 7 skin skin NOUN cana-616 199 8 disease disease NOUN cana-616 199 9 , , PUNCT cana-616 199 10 several several ADJ cana-616 199 11 algorithms algorithm NOUN cana-616 199 12 could could AUX cana-616 199 13 be be AUX cana-616 199 14 considered consider VERB cana-616 199 15 : : PUNCT cana-616 199 16 β€’ β€’ NUM cana-616 199 17 logistic logistic ADJ cana-616 199 18 regression regression NOUN cana-616 199 19 is be AUX cana-616 199 20 a a DET cana-616 199 21 baseline baseline NOUN cana-616 199 22 for for ADP cana-616 199 23 binary binary ADJ cana-616 199 24 classification classification NOUN cana-616 199 25 problems problem NOUN cana-616 199 26 . . PUNCT cana-616 200 1 β€’ β€’ NUM cana-616 200 2 decision decision NOUN cana-616 200 3 trees tree NOUN cana-616 200 4 and and CCONJ cana-616 200 5 random random ADJ cana-616 200 6 forests forest NOUN cana-616 200 7 offer offer VERB cana-616 200 8 robustness robustness NOUN cana-616 200 9 through through ADP cana-616 200 10 their their PRON cana-616 200 11 non non ADJ cana-616 200 12 - - ADJ cana-616 200 13 linear linear ADJ cana-616 200 14 nature nature NOUN cana-616 200 15 and and CCONJ cana-616 200 16 ability ability NOUN cana-616 200 17 to to PART cana-616 200 18 handle handle VERB cana-616 200 19 complex complex ADJ cana-616 200 20 interactions interaction NOUN cana-616 200 21 between between ADP cana-616 200 22 features feature NOUN cana-616 200 23 . . PUNCT cana-616 201 1 β€’ β€’ NOUN cana-616 201 2 support support NOUN cana-616 201 3 vector vector NOUN cana-616 201 4 machines machine NOUN cana-616 201 5 provide provide VERB cana-616 201 6 effectiveness effectiveness NOUN cana-616 201 7 in in ADP cana-616 201 8 high high ADJ cana-616 201 9 - - PUNCT cana-616 201 10 dimensional dimensional ADJ cana-616 201 11 spaces space NOUN cana-616 201 12 . . PUNCT cana-616 202 1 communications communication NOUN cana-616 202 2 on on ADP cana-616 202 3 applied apply VERB cana-616 202 4 nonlinear nonlinear ADJ cana-616 202 5 analysis analysis NOUN cana-616 202 6 issn issn NOUN cana-616 202 7 : : PUNCT cana-616 202 8 1074 1074 NUM cana-616 202 9 - - PUNCT cana-616 202 10 133x 133x NUM cana-616 202 11 vol vol NOUN cana-616 202 12 31 31 NUM cana-616 202 13 no no NOUN cana-616 202 14 . . PUNCT cana-616 203 1 2s 2s NUM cana-616 203 2 ( ( PUNCT cana-616 203 3 2024 2024 NUM cana-616 203 4 ) ) PUNCT cana-616 203 5 131 131 NUM cana-616 203 6 https://internationalpubls.com https://internationalpubls.com SYM cana-616 203 7 β€’ β€’ NOUN cana-616 203 8 neural neural ADJ cana-616 203 9 networks network NOUN cana-616 203 10 offer offer VERB cana-616 203 11 high high ADJ cana-616 203 12 flexibility flexibility NOUN cana-616 203 13 and and CCONJ cana-616 203 14 capability capability NOUN cana-616 203 15 to to PART cana-616 203 16 model model VERB cana-616 203 17 non non ADJ cana-616 203 18 - - ADJ cana-616 203 19 linear linear ADJ cana-616 203 20 relationships relationship NOUN cana-616 203 21 at at ADP cana-616 203 22 the the DET cana-616 203 23 expense expense NOUN cana-616 203 24 of of ADP cana-616 203 25 requiring require VERB cana-616 203 26 large large ADJ cana-616 203 27 datasets dataset NOUN cana-616 203 28 and and CCONJ cana-616 203 29 computational computational ADJ cana-616 203 30 resources resource NOUN cana-616 203 31 . . PUNCT cana-616 204 1 model model NOUN cana-616 204 2 training training NOUN cana-616 204 3 and and CCONJ cana-616 204 4 validation validation NOUN cana-616 204 5 during during ADP cana-616 204 6 the the DET cana-616 204 7 training training NOUN cana-616 204 8 phase phase NOUN cana-616 204 9 a a DET cana-616 204 10 model model NOUN cana-616 204 11 same same ADJ cana-616 204 12 thing thing NOUN cana-616 204 13 is be AUX cana-616 204 14 done do VERB cana-616 204 15 , , PUNCT cana-616 204 16 and and CCONJ cana-616 204 17 a a DET cana-616 204 18 part part NOUN cana-616 204 19 of of ADP cana-616 204 20 the the DET cana-616 204 21 data datum NOUN cana-616 204 22 is be AUX cana-616 204 23 set set VERB cana-616 204 24 apart apart ADV cana-616 204 25 to to PART cana-616 204 26 learn learn VERB cana-616 204 27 the the DET cana-616 204 28 features feature NOUN cana-616 204 29 characteristics characteristic NOUN cana-616 204 30 the the DET cana-616 204 31 outcomes outcome NOUN cana-616 204 32 also also ADV cana-616 204 33 . . PUNCT cana-616 205 1 eventually eventually ADV cana-616 205 2 , , PUNCT cana-616 205 3 validation validation NOUN cana-616 205 4 gauges gauge VERB cana-616 205 5 performance performance NOUN cana-616 205 6 on on ADP cana-616 205 7 data datum NOUN cana-616 205 8 it it PRON cana-616 205 9 never never ADV cana-616 205 10 saw see VERB cana-616 205 11 , , PUNCT cana-616 205 12 which which PRON cana-616 205 13 checks check VERB cana-616 205 14 for for ADP cana-616 205 15 generalization generalization NOUN cana-616 205 16 . . PUNCT cana-616 206 1 approaches approach NOUN cana-616 206 2 such such ADJ cana-616 206 3 as as ADP cana-616 206 4 k k ADJ cana-616 206 5 - - ADJ cana-616 206 6 fold fold ADJ cana-616 206 7 cross cross NOUN cana-616 206 8 - - NOUN cana-616 206 9 validation validation NOUN cana-616 206 10 is be AUX cana-616 206 11 critically critically ADV cana-616 206 12 vital vital ADJ cana-616 206 13 for for ADP cana-616 206 14 not not PART cana-616 206 15 just just ADV cana-616 206 16 validating validate VERB cana-616 206 17 the the DET cana-616 206 18 model model NOUN cana-616 206 19 across across ADP cana-616 206 20 many many ADJ cana-616 206 21 random random ADJ cana-616 206 22 data datum NOUN cana-616 206 23 subsets subset NOUN cana-616 206 24 but but CCONJ cana-616 206 25 also also ADV cana-616 206 26 for for ADP cana-616 206 27 making make VERB cana-616 206 28 sure sure ADJ cana-616 206 29 a a DET cana-616 206 30 model model NOUN cana-616 206 31 is be AUX cana-616 206 32 stable stable ADJ cana-616 206 33 and and CCONJ cana-616 206 34 reliable reliable ADJ cana-616 206 35 , , PUNCT cana-616 206 36 whose whose DET cana-616 206 37 predictions prediction NOUN cana-616 206 38 are be AUX cana-616 206 39 replicable replicable ADJ cana-616 206 40 . . PUNCT cana-616 207 1 apart apart ADV cana-616 207 2 from from ADP cana-616 207 3 this this PRON cana-616 207 4 , , PUNCT cana-616 207 5 perfecting perfect VERB cana-616 207 6 the the DET cana-616 207 7 parameter parameter NOUN cana-616 207 8 of of ADP cana-616 207 9 the the DET cana-616 207 10 model model NOUN cana-616 207 11 itself itself PRON cana-616 207 12 through through ADP cana-616 207 13 grid grid NOUN cana-616 207 14 search search NOUN cana-616 207 15 or or CCONJ cana-616 207 16 by by ADP cana-616 207 17 randomized randomized ADJ cana-616 207 18 search search NOUN cana-616 207 19 enable enable VERB cana-616 207 20 the the DET cana-616 207 21 model model NOUN cana-616 207 22 to to PART cana-616 207 23 be be AUX cana-616 207 24 executed execute VERB cana-616 207 25 at at ADP cana-616 207 26 its its PRON cana-616 207 27 optimal optimal ADJ cana-616 207 28 performance performance NOUN cana-616 207 29 . . PUNCT cana-616 208 1 figure figure NOUN cana-616 208 2 3 3 NUM cana-616 208 3 : : PUNCT cana-616 208 4 flow flow VERB cana-616 208 5 chart chart NOUN cana-616 208 6 model model NOUN cana-616 208 7 training training NOUN cana-616 208 8 and and CCONJ cana-616 208 9 validation validation NOUN cana-616 208 10 communications communication NOUN cana-616 208 11 on on ADP cana-616 208 12 applied apply VERB cana-616 208 13 nonlinear nonlinear ADJ cana-616 208 14 analysis analysis NOUN cana-616 208 15 issn issn NOUN cana-616 208 16 : : PUNCT cana-616 208 17 1074 1074 NUM cana-616 208 18 - - PUNCT cana-616 208 19 133x 133x NUM cana-616 208 20 vol vol NOUN cana-616 208 21 31 31 NUM cana-616 208 22 no no NOUN cana-616 208 23 . . PUNCT cana-616 209 1 2s 2s NUM cana-616 209 2 ( ( PUNCT cana-616 209 3 2024 2024 NUM cana-616 209 4 ) ) PUNCT cana-616 209 5 132 132 NUM cana-616 209 6 https://internationalpubls.com https://internationalpubls.com X cana-616 209 7 figure figure NOUN cana-616 209 8 4 4 NUM cana-616 209 9 : : PUNCT cana-616 209 10 flow flow VERB cana-616 209 11 chart chart NOUN cana-616 209 12 for for ADP cana-616 209 13 learning learn VERB cana-616 209 14 algorithm algorithm NOUN cana-616 209 15 model model NOUN cana-616 209 16 optimization optimization NOUN cana-616 209 17 along along ADP cana-616 209 18 with with ADP cana-616 209 19 that that PRON cana-616 209 20 , , PUNCT cana-616 209 21 the the DET cana-616 209 22 optimization optimization NOUN cana-616 209 23 of of ADP cana-616 209 24 the the DET cana-616 209 25 best well ADV cana-616 209 26 fitted fit VERB cana-616 209 27 model model NOUN cana-616 209 28 includes include VERB cana-616 209 29 ensemble ensemble ADJ cana-616 209 30 techniques technique NOUN cana-616 209 31 like like ADP cana-616 209 32 bagging bagging NOUN cana-616 209 33 , , PUNCT cana-616 209 34 boosting boost VERB cana-616 209 35 or or CCONJ cana-616 209 36 stacking stacking NOUN cana-616 209 37 which which PRON cana-616 209 38 can can AUX cana-616 209 39 be be AUX cana-616 209 40 applied apply VERB cana-616 209 41 to to PART cana-616 209 42 improve improve VERB cana-616 209 43 the the DET cana-616 209 44 model model NOUN cana-616 209 45 accuracy accuracy NOUN cana-616 209 46 and and CCONJ cana-616 209 47 to to PART cana-616 209 48 reduce reduce VERB cana-616 209 49 the the DET cana-616 209 50 chance chance NOUN cana-616 209 51 of of ADP cana-616 209 52 the the DET cana-616 209 53 model model NOUN cana-616 209 54 overfitting overfitting NOUN cana-616 209 55 . . PUNCT cana-616 210 1 these these DET cana-616 210 2 methods method NOUN cana-616 210 3 use use VERB cana-616 210 4 an an DET cana-616 210 5 ensemble ensemble NOUN cana-616 210 6 of of ADP cana-616 210 7 different different ADJ cana-616 210 8 weak weak ADJ cana-616 210 9 model model NOUN cana-616 210 10 to to ADP cana-616 210 11 a a DET cana-616 210 12 create create NOUN cana-616 210 13 a a DET cana-616 210 14 robust robust ADJ cana-616 210 15 predictor predictor NOUN cana-616 210 16 . . PUNCT cana-616 211 1 further far ADV cana-616 211 2 , , PUNCT cana-616 211 3 handling handle VERB cana-616 211 4 unbalanced unbalanced ADJ cana-616 211 5 data datum NOUN cana-616 211 6 sets set NOUN cana-616 211 7 with with ADP cana-616 211 8 the the DET cana-616 211 9 techniques technique NOUN cana-616 211 10 like like ADP cana-616 211 11 smote smote NOUN cana-616 211 12 ( ( PUNCT cana-616 211 13 synthetic synthetic ADJ cana-616 211 14 minority minority NOUN cana-616 211 15 over over ADP cana-616 211 16 - - PUNCT cana-616 211 17 sampling sample VERB cana-616 211 18 technique technique NOUN cana-616 211 19 ) ) PUNCT cana-616 211 20 enables enable VERB cana-616 211 21 to to PART cana-616 211 22 improve improve VERB cana-616 211 23 the the DET cana-616 211 24 detection detection NOUN cana-616 211 25 ability ability NOUN cana-616 211 26 of of ADP cana-616 211 27 the the DET cana-616 211 28 model model NOUN cana-616 211 29 particularly particularly ADV cana-616 211 30 that that PRON cana-616 211 31 of of ADP cana-616 211 32 the the DET cana-616 211 33 less less ADV cana-616 211 34 frequent frequent ADJ cana-616 211 35 class class NOUN cana-616 211 36 , , PUNCT cana-616 211 37 which which PRON cana-616 211 38 is be AUX cana-616 211 39 usually usually ADV cana-616 211 40 positive positive ADJ cana-616 211 41 class class NOUN cana-616 211 42 in in ADP cana-616 211 43 medical medical ADJ cana-616 211 44 diagnosis diagnosis NOUN cana-616 211 45 . . PUNCT cana-616 212 1 communications communication NOUN cana-616 212 2 on on ADP cana-616 212 3 applied apply VERB cana-616 212 4 nonlinear nonlinear ADJ cana-616 212 5 analysis analysis NOUN cana-616 212 6 issn issn NOUN cana-616 212 7 : : PUNCT cana-616 212 8 1074 1074 NUM cana-616 212 9 - - PUNCT cana-616 212 10 133x 133x NUM cana-616 212 11 vol vol NOUN cana-616 212 12 31 31 NUM cana-616 212 13 no no NOUN cana-616 212 14 . . PUNCT cana-616 213 1 2s 2s NUM cana-616 213 2 ( ( PUNCT cana-616 213 3 2024 2024 NUM cana-616 213 4 ) ) PUNCT cana-616 213 5 133 133 NUM cana-616 213 6 https://internationalpubls.com https://internationalpubls.com X cana-616 213 7 deployment deployment NOUN cana-616 213 8 the the DET cana-616 213 9 final final ADJ cana-616 213 10 model model NOUN cana-616 213 11 is be AUX cana-616 213 12 then then ADV cana-616 213 13 ready ready ADJ cana-616 213 14 for for ADP cana-616 213 15 deployment deployment NOUN cana-616 213 16 into into ADP cana-616 213 17 a a DET cana-616 213 18 production production NOUN cana-616 213 19 environment environment NOUN cana-616 213 20 , , PUNCT cana-616 213 21 and and CCONJ cana-616 213 22 can can AUX cana-616 213 23 be be AUX cana-616 213 24 employed employ VERB cana-616 213 25 to to PART cana-616 213 26 predict predict VERB cana-616 213 27 on on ADP cana-616 213 28 new new ADJ cana-616 213 29 data datum NOUN cana-616 213 30 . . PUNCT cana-616 214 1 this this PRON cana-616 214 2 could could AUX cana-616 214 3 be be AUX cana-616 214 4 incorporated incorporate VERB cana-616 214 5 together together ADV cana-616 214 6 with with ADP cana-616 214 7 veterinary veterinary ADJ cana-616 214 8 diagnostics diagnostic NOUN cana-616 214 9 and and CCONJ cana-616 214 10 make make VERB cana-616 214 11 the the DET cana-616 214 12 analysis analysis NOUN cana-616 214 13 faster fast ADV cana-616 214 14 and and CCONJ cana-616 214 15 more more ADV cana-616 214 16 accurate accurate ADJ cana-616 214 17 , , PUNCT cana-616 214 18 such such DET cana-616 214 19 a a DET cana-616 214 20 feature feature NOUN cana-616 214 21 would would AUX cana-616 214 22 be be AUX cana-616 214 23 very very ADV cana-616 214 24 useful useful ADJ cana-616 214 25 for for ADP cana-616 214 26 diagnosis diagnosis NOUN cana-616 214 27 of of ADP cana-616 214 28 the the DET cana-616 214 29 lumpy lumpy ADJ cana-616 214 30 skin skin NOUN cana-616 214 31 disease disease NOUN cana-616 214 32 . . PUNCT cana-616 215 1 not not PART cana-616 215 2 only only ADV cana-616 215 3 must must AUX cana-616 215 4 we we PRON cana-616 215 5 implement implement VERB cana-616 215 6 a a DET cana-616 215 7 system system NOUN cana-616 215 8 for for ADP cana-616 215 9 regularly regularly ADV cana-616 215 10 monitoring monitor VERB cana-616 215 11 the the DET cana-616 215 12 model model NOUN cana-616 215 13 's 's PART cana-616 215 14 performance performance NOUN cana-616 215 15 , , PUNCT cana-616 215 16 but but CCONJ cana-616 215 17 also also ADV cana-616 215 18 we we PRON cana-616 215 19 need need VERB cana-616 215 20 to to PART cana-616 215 21 update update VERB cana-616 215 22 the the DET cana-616 215 23 model model NOUN cana-616 215 24 when when SCONJ cana-616 215 25 new new ADJ cana-616 215 26 datasets dataset NOUN cana-616 215 27 are be AUX cana-616 215 28 available available ADJ cana-616 215 29 or or CCONJ cana-616 215 30 the the DET cana-616 215 31 course course NOUN cana-616 215 32 of of ADP cana-616 215 33 the the DET cana-616 215 34 disease disease NOUN cana-616 215 35 changes change VERB cana-616 215 36 . . PUNCT cana-616 216 1 in in ADP cana-616 216 2 sum sum NOUN cana-616 216 3 , , PUNCT cana-616 216 4 the the DET cana-616 216 5 methodology methodology NOUN cana-616 216 6 drafted draft VERB cana-616 216 7 can can AUX cana-616 216 8 be be AUX cana-616 216 9 regarded regard VERB cana-616 216 10 as as ADP cana-616 216 11 a a DET cana-616 216 12 worthy worthy ADJ cana-616 216 13 tool tool NOUN cana-616 216 14 for for ADP cana-616 216 15 the the DET cana-616 216 16 development development NOUN cana-616 216 17 of of ADP cana-616 216 18 a a DET cana-616 216 19 machinelearning machinelearning NOUN cana-616 216 20 model model NOUN cana-616 216 21 for for ADP cana-616 216 22 the the DET cana-616 216 23 classification classification NOUN cana-616 216 24 of of ADP cana-616 216 25 lumpy lumpy ADJ cana-616 216 26 skin skin NOUN cana-616 216 27 disease disease NOUN cana-616 216 28 in in ADP cana-616 216 29 livestock livestock NOUN cana-616 216 30 . . PUNCT cana-616 217 1 in in ADP cana-616 217 2 futher futher NOUN cana-616 217 3 developments development NOUN cana-616 217 4 we we PRON cana-616 217 5 can can AUX cana-616 217 6 consider consider VERB cana-616 217 7 the the DET cana-616 217 8 use use NOUN cana-616 217 9 of of ADP cana-616 217 10 additional additional ADJ cana-616 217 11 datasets dataset NOUN cana-616 217 12 from from ADP cana-616 217 13 different different ADJ cana-616 217 14 sources source NOUN cana-616 217 15 as as ADV cana-616 217 16 well well ADV cana-616 217 17 as as ADP cana-616 217 18 the the DET cana-616 217 19 application application NOUN cana-616 217 20 of of ADP cana-616 217 21 advanced advanced ADJ cana-616 217 22 machine machine NOUN cana-616 217 23 learning learning NOUN cana-616 217 24 and and CCONJ cana-616 217 25 deep deep ADJ cana-616 217 26 learning learning NOUN cana-616 217 27 algorithms algorithm NOUN cana-616 217 28 while while SCONJ cana-616 217 29 also also ADV cana-616 217 30 improving improve VERB cana-616 217 31 the the DET cana-616 217 32 model model NOUN cana-616 217 33 to to PART cana-616 217 34 cover cover VERB cana-616 217 35 later later ADJ cana-616 217 36 stages stage NOUN cana-616 217 37 of of ADP cana-616 217 38 the the DET cana-616 217 39 disease disease NOUN cana-616 217 40 or or CCONJ cana-616 217 41 patient patient NOUN cana-616 217 42 ’s ’s PART cana-616 217 43 responses response NOUN cana-616 217 44 to to ADP cana-616 217 45 different different ADJ cana-616 217 46 treatments treatment NOUN cana-616 217 47 . . PUNCT cana-616 218 1 such such DET cana-616 218 2 a a DET cana-616 218 3 continuous continuous ADJ cana-616 218 4 evolution evolution NOUN cana-616 218 5 of of ADP cana-616 218 6 the the DET cana-616 218 7 model model NOUN cana-616 218 8 will will AUX cana-616 218 9 be be AUX cana-616 218 10 the the DET cana-616 218 11 guarantee guarantee NOUN cana-616 218 12 of of ADP cana-616 218 13 its its PRON cana-616 218 14 efficiency efficiency NOUN cana-616 218 15 and and CCONJ cana-616 218 16 its its PRON cana-616 218 17 actuality actuality NOUN cana-616 218 18 concerned concern VERB cana-616 218 19 with with ADP cana-616 218 20 the the DET cana-616 218 21 fast fast ADJ cana-616 218 22 change change NOUN cana-616 218 23 in in ADP cana-616 218 24 the the DET cana-616 218 25 veterinary veterinary ADJ cana-616 218 26 environment environment NOUN cana-616 218 27 and and CCONJ cana-616 218 28 with with ADP cana-616 218 29 the the DET cana-616 218 30 new new ADJ cana-616 218 31 challenges challenge NOUN cana-616 218 32 which which PRON cana-616 218 33 emerge emerge VERB cana-616 218 34 in in ADP cana-616 218 35 this this DET cana-616 218 36 field field NOUN cana-616 218 37 . . PUNCT cana-616 219 1 the the DET cana-616 219 2 outcomes outcome NOUN cana-616 219 3 and and CCONJ cana-616 219 4 discussion discussion NOUN cana-616 219 5 presented present VERB cana-616 219 6 based base VERB cana-616 219 7 on on ADP cana-616 219 8 the the DET cana-616 219 9 study study NOUN cana-616 219 10 with with ADP cana-616 219 11 machine machine NOUN cana-616 219 12 learning learn VERB cana-616 219 13 approaches approach NOUN cana-616 219 14 and and CCONJ cana-616 219 15 statistical statistical ADJ cana-616 219 16 models model NOUN cana-616 219 17 are be AUX cana-616 219 18 crucial crucial ADJ cana-616 219 19 in in ADP cana-616 219 20 grasping grasp VERB cana-616 219 21 the the DET cana-616 219 22 epidemiology epidemiology NOUN cana-616 219 23 , , PUNCT cana-616 219 24 risk risk NOUN cana-616 219 25 factors factor NOUN cana-616 219 26 and and CCONJ cana-616 219 27 dynamics dynamic NOUN cana-616 219 28 of of ADP cana-616 219 29 the the DET cana-616 219 30 lumpy lumpy ADJ cana-616 219 31 skin skin NOUN cana-616 219 32 disease disease NOUN cana-616 219 33 ( ( PUNCT cana-616 219 34 lsd lsd NOUN cana-616 219 35 ) ) PUNCT cana-616 219 36 . . PUNCT cana-616 220 1 by by ADP cana-616 220 2 using use VERB cana-616 220 3 a a DET cana-616 220 4 variety variety NOUN cana-616 220 5 of of ADP cana-616 220 6 methods method NOUN cana-616 220 7 , , PUNCT cana-616 220 8 ranging range VERB cana-616 220 9 from from ADP cana-616 220 10 exploratory exploratory ADJ cana-616 220 11 data datum NOUN cana-616 220 12 analysis analysis NOUN cana-616 220 13 to to ADP cana-616 220 14 complex complex ADJ cana-616 220 15 model model NOUN cana-616 220 16 prediction prediction NOUN cana-616 220 17 , , PUNCT cana-616 220 18 researchers researcher NOUN cana-616 220 19 usually usually ADV cana-616 220 20 end end VERB cana-616 220 21 up up ADP cana-616 220 22 with with ADP cana-616 220 23 a a DET cana-616 220 24 well well ADV cana-616 220 25 - - PUNCT cana-616 220 26 rounded rounded ADJ cana-616 220 27 and and CCONJ cana-616 220 28 thorough thorough ADJ cana-616 220 29 portrayal portrayal NOUN cana-616 220 30 of of ADP cana-616 220 31 the the DET cana-616 220 32 features feature NOUN cana-616 220 33 and and CCONJ cana-616 220 34 consequences consequence NOUN cana-616 220 35 of of ADP cana-616 220 36 the the DET cana-616 220 37 disease disease NOUN cana-616 220 38 . . PUNCT cana-616 221 1 i i PRON cana-616 221 2 provide provide VERB cana-616 221 3 detailed detailed ADJ cana-616 221 4 analyses analysis NOUN cana-616 221 5 of of ADP cana-616 221 6 these these DET cana-616 221 7 results result NOUN cana-616 221 8 in in ADP cana-616 221 9 the the DET cana-616 221 10 paragraphs paragraph NOUN cana-616 221 11 that that PRON cana-616 221 12 follow follow VERB cana-616 221 13 . . PUNCT cana-616 222 1 : : PUNCT cana-616 222 2 figure figure VERB cana-616 222 3 5 5 NUM cana-616 222 4 : : PUNCT cana-616 222 5 lumpy lumpy ADJ cana-616 222 6 skin skin NOUN cana-616 222 7 disease disease NOUN cana-616 222 8 by by ADP cana-616 222 9 region region NOUN cana-616 222 10 wise wise ADJ cana-616 222 11 v v ADP cana-616 222 12 / / SYM cana-616 222 13 s s NOUN cana-616 222 14 no no NOUN cana-616 222 15 . . PUNCT cana-616 223 1 of of ADP cana-616 223 2 lsd lsd NOUN cana-616 223 3 cases case NOUN cana-616 223 4 this this DET cana-616 223 5 part part NOUN cana-616 223 6 deals deal VERB cana-616 223 7 with with ADP cana-616 223 8 the the DET cana-616 223 9 main main ADJ cana-616 223 10 observations observation NOUN cana-616 223 11 resulting result VERB cana-616 223 12 from from ADP cana-616 223 13 the the DET cana-616 223 14 datasets dataset NOUN cana-616 223 15 combined combine VERB cana-616 223 16 with with ADP cana-616 223 17 the the DET cana-616 223 18 analysis analysis NOUN cana-616 223 19 that that PRON cana-616 223 20 is be AUX cana-616 223 21 concerned concern VERB cana-616 223 22 with with ADP cana-616 223 23 locations location NOUN cana-616 223 24 , , PUNCT cana-616 223 25 regions region NOUN cana-616 223 26 , , PUNCT cana-616 223 27 populations population NOUN cana-616 223 28 ( ( PUNCT cana-616 223 29 by by ADP cana-616 223 30 age age NOUN cana-616 223 31 , , PUNCT cana-616 223 32 gender gender NOUN cana-616 223 33 , , PUNCT cana-616 223 34 and and CCONJ cana-616 223 35 economic economic ADJ cana-616 223 36 groups group NOUN cana-616 223 37 ) ) PUNCT cana-616 223 38 that that PRON cana-616 223 39 are be AUX cana-616 223 40 affected affect VERB cana-616 223 41 by by ADP cana-616 223 42 the the DET cana-616 223 43 lumpy lumpy ADJ cana-616 223 44 skin skin NOUN cana-616 223 45 disease disease NOUN cana-616 223 46 illness illness NOUN cana-616 223 47 . . PUNCT cana-616 224 1 these these DET cana-616 224 2 outcomes outcome NOUN cana-616 224 3 are be AUX cana-616 224 4 gained gain VERB cana-616 224 5 from from ADP cana-616 224 6 the the DET cana-616 224 7 initial initial ADJ cana-616 224 8 exploratory exploratory ADJ cana-616 224 9 data datum NOUN cana-616 224 10 analysis analysis NOUN cana-616 224 11 that that PRON cana-616 224 12 are be AUX cana-616 224 13 used use VERB cana-616 224 14 as as ADP cana-616 224 15 a a DET cana-616 224 16 basis basis NOUN cana-616 224 17 for for ADP cana-616 224 18 further further ADJ cana-616 224 19 inferential inferential ADJ cana-616 224 20 statistics statistic NOUN cana-616 224 21 and and CCONJ cana-616 224 22 machine machine NOUN cana-616 224 23 learning learning NOUN cana-616 224 24 models model NOUN cana-616 224 25 which which PRON cana-616 224 26 are be AUX cana-616 224 27 made make VERB cana-616 224 28 extremely extremely ADV cana-616 224 29 accurate accurate ADJ cana-616 224 30 to to PART cana-616 224 31 control control VERB cana-616 224 32 the the DET cana-616 224 33 behavior behavior NOUN cana-616 224 34 of of ADP cana-616 224 35 the the DET cana-616 224 36 disease disease NOUN cana-616 224 37 and and CCONJ cana-616 224 38 even even ADV cana-616 224 39 predict predict VERB cana-616 224 40 future future ADJ cana-616 224 41 outbreaks outbreak NOUN cana-616 224 42 . . PUNCT cana-616 225 1 communications communication NOUN cana-616 225 2 on on ADP cana-616 225 3 applied apply VERB cana-616 225 4 nonlinear nonlinear ADJ cana-616 225 5 analysis analysis NOUN cana-616 225 6 issn issn NOUN cana-616 225 7 : : PUNCT cana-616 225 8 1074 1074 NUM cana-616 225 9 - - PUNCT cana-616 225 10 133x 133x NUM cana-616 225 11 vol vol NOUN cana-616 225 12 31 31 NUM cana-616 225 13 no no NOUN cana-616 225 14 . . PUNCT cana-616 226 1 2s 2s NUM cana-616 226 2 ( ( PUNCT cana-616 226 3 2024 2024 NUM cana-616 226 4 ) ) PUNCT cana-616 226 5 134 134 NUM cana-616 226 6 https://internationalpubls.com https://internationalpubls.com X cana-616 226 7 figure figure NOUN cana-616 226 8 6 6 NUM cana-616 226 9 : : PUNCT cana-616 226 10 correlation correlation NOUN cana-616 226 11 heatmap heatmap NOUN cana-616 226 12 of of ADP cana-616 226 13 climate climate NOUN cana-616 226 14 variables variable NOUN cana-616 226 15 with with ADP cana-616 226 16 lsd lsd NOUN cana-616 226 17 distribution distribution NOUN cana-616 226 18 and and CCONJ cana-616 226 19 descriptive descriptive ADJ cana-616 226 20 statistics statistic NOUN cana-616 226 21 : : PUNCT cana-616 226 22 the the DET cana-616 226 23 primary primary ADJ cana-616 226 24 phase phase NOUN cana-616 226 25 of of ADP cana-616 226 26 eda eda PROPN cana-616 226 27 would would AUX cana-616 226 28 include include VERB cana-616 226 29 data datum NOUN cana-616 226 30 exploration exploration NOUN cana-616 226 31 by by ADP cana-616 226 32 plotting plot VERB cana-616 226 33 lsd lsd NOUN cana-616 226 34 on on ADP cana-616 226 35 different different ADJ cana-616 226 36 factors factor NOUN cana-616 226 37 especially especially ADV cana-616 226 38 location location NOUN cana-616 226 39 , , PUNCT cana-616 226 40 time time NOUN cana-616 226 41 , , PUNCT cana-616 226 42 age age NOUN cana-616 226 43 of of ADP cana-616 226 44 animals animal NOUN cana-616 226 45 , , PUNCT cana-616 226 46 development development NOUN cana-616 226 47 among among ADP cana-616 226 48 others other NOUN cana-616 226 49 . . PUNCT cana-616 227 1 histograms histogram NOUN cana-616 227 2 , , PUNCT cana-616 227 3 box box NOUN cana-616 227 4 plots plot NOUN cana-616 227 5 , , PUNCT cana-616 227 6 and and CCONJ cana-616 227 7 other other ADJ cana-616 227 8 forms form NOUN cana-616 227 9 of of ADP cana-616 227 10 graphical graphical ADJ cana-616 227 11 representations representation NOUN cana-616 227 12 present present VERB cana-616 227 13 a a DET cana-616 227 14 visual visual ADJ cana-616 227 15 armory armory NOUN cana-616 227 16 about about ADP cana-616 227 17 occurrence occurrence NOUN cana-616 227 18 of of ADP cana-616 227 19 these these DET cana-616 227 20 diseases disease NOUN cana-616 227 21 , , PUNCT cana-616 227 22 thus thus ADV cana-616 227 23 provide provide VERB cana-616 227 24 useful useful ADJ cana-616 227 25 information information NOUN cana-616 227 26 on on ADP cana-616 227 27 the the DET cana-616 227 28 distribution distribution NOUN cana-616 227 29 of of ADP cana-616 227 30 a a DET cana-616 227 31 disease disease NOUN cana-616 227 32 and and CCONJ cana-616 227 33 also also ADV cana-616 227 34 areas area NOUN cana-616 227 35 or or CCONJ cana-616 227 36 populations population NOUN cana-616 227 37 with with ADP cana-616 227 38 high high ADJ cana-616 227 39 incidences incidence NOUN cana-616 227 40 . . PUNCT cana-616 228 1 statistical statistical ADJ cana-616 228 2 descriptors descriptor NOUN cana-616 228 3 of of ADP cana-616 228 4 all all DET cana-616 228 5 clinical clinical ADJ cana-616 228 6 parameters parameter NOUN cana-616 228 7 and and CCONJ cana-616 228 8 outcomes outcome NOUN cana-616 228 9 are be AUX cana-616 228 10 calculated calculate VERB cana-616 228 11 in in ADP cana-616 228 12 order order NOUN cana-616 228 13 to to PART cana-616 228 14 have have AUX cana-616 228 15 a a DET cana-616 228 16 broad broad ADJ cana-616 228 17 understanding understanding NOUN cana-616 228 18 of of ADP cana-616 228 19 trends trend NOUN cana-616 228 20 and and CCONJ cana-616 228 21 relationships relationship NOUN cana-616 228 22 in in ADP cana-616 228 23 the the DET cana-616 228 24 data datum NOUN cana-616 228 25 which which PRON cana-616 228 26 further far ADV cana-616 228 27 calls call VERB cana-616 228 28 for for ADP cana-616 228 29 more more ADV cana-616 228 30 analytical analytical ADJ cana-616 228 31 introspective introspective ADJ cana-616 228 32 . . PUNCT cana-616 229 1 correlation correlation NOUN cana-616 229 2 analysis analysis NOUN cana-616 229 3 : : PUNCT cana-616 229 4 it it PRON cana-616 229 5 is be AUX cana-616 229 6 important important ADJ cana-616 229 7 to to PART cana-616 229 8 trace trace VERB cana-616 229 9 the the DET cana-616 229 10 links link NOUN cana-616 229 11 between between ADP cana-616 229 12 the the DET cana-616 229 13 environment environment NOUN cana-616 229 14 , , PUNCT cana-616 229 15 physiological physiological ADJ cana-616 229 16 features feature NOUN cana-616 229 17 and and CCONJ cana-616 229 18 the the DET cana-616 229 19 number number NOUN cana-616 229 20 of of ADP cana-616 229 21 lsd lsd NOUN cana-616 229 22 instances instance NOUN cana-616 229 23 so so SCONJ cana-616 229 24 that that SCONJ cana-616 229 25 one one PRON cana-616 229 26 can can AUX cana-616 229 27 identify identify VERB cana-616 229 28 any any DET cana-616 229 29 correlations correlation NOUN cana-616 229 30 among among ADP cana-616 229 31 them they PRON cana-616 229 32 . . PUNCT cana-616 230 1 heatmaps heatmap NOUN cana-616 230 2 and and CCONJ cana-616 230 3 scatterplots scatterplot NOUN cana-616 230 4 , , PUNCT cana-616 230 5 in in ADP cana-616 230 6 this this DET cana-616 230 7 respect respect NOUN cana-616 230 8 , , PUNCT cana-616 230 9 are be AUX cana-616 230 10 the the DET cana-616 230 11 indispensable indispensable ADJ cana-616 230 12 data datum NOUN cana-616 230 13 visualization visualization NOUN cana-616 230 14 tools tool NOUN cana-616 230 15 which which PRON cana-616 230 16 range range VERB cana-616 230 17 from from ADP cana-616 230 18 demonstrating demonstrate VERB cana-616 230 19 these these DET cana-616 230 20 correlations correlation NOUN cana-616 230 21 to to ADP cana-616 230 22 some some DET cana-616 230 23 areas area NOUN cana-616 230 24 where where SCONJ cana-616 230 25 further further ADJ cana-616 230 26 research research NOUN cana-616 230 27 is be AUX cana-616 230 28 needed need VERB cana-616 230 29 or or CCONJ cana-616 230 30 interventions intervention NOUN cana-616 230 31 should should AUX cana-616 230 32 be be AUX cana-616 230 33 made make VERB cana-616 230 34 . . PUNCT cana-616 231 1 analytical analytical ADJ cana-616 231 2 testing testing NOUN cana-616 231 3 : : PUNCT cana-616 232 1 complex complex ADJ cana-616 232 2 mathematical mathematical ADJ cana-616 232 3 methods method NOUN cana-616 232 4 of of ADP cana-616 232 5 the the DET cana-616 232 6 type type NOUN cana-616 232 7 chi chi ADJ cana-616 232 8 - - PUNCT cana-616 232 9 square square ADJ cana-616 232 10 tests test NOUN cana-616 232 11 , , PUNCT cana-616 232 12 t t NOUN cana-616 232 13 - - PUNCT cana-616 232 14 test test NOUN cana-616 232 15 , , PUNCT cana-616 232 16 and and CCONJ cana-616 232 17 anova anova PROPN cana-616 232 18 are be AUX cana-616 232 19 performed perform VERB cana-616 232 20 to to PART cana-616 232 21 verify verify VERB cana-616 232 22 hypotheses hypothesis NOUN cana-616 232 23 of of ADP cana-616 232 24 lsd lsd NOUN cana-616 232 25 prevalence prevalence NOUN cana-616 232 26 among among ADP cana-616 232 27 different different ADJ cana-616 232 28 groups group NOUN cana-616 232 29 which which PRON cana-616 232 30 are be AUX cana-616 232 31 differentiated differentiate VERB cana-616 232 32 through through ADP cana-616 232 33 three three NUM cana-616 232 34 groups group NOUN cana-616 232 35 of of ADP cana-616 232 36 variables variable NOUN cana-616 232 37 – – PUNCT cana-616 232 38 geographical geographical ADJ cana-616 232 39 area area NOUN cana-616 232 40 , , PUNCT cana-616 232 41 breed breed NOUN cana-616 232 42 / / SYM cana-616 232 43 species specie NOUN cana-616 232 44 , , PUNCT cana-616 232 45 and and CCONJ cana-616 232 46 age age NOUN cana-616 232 47 . . PUNCT cana-616 233 1 oftentimes oftentime VERB cana-616 233 2 the the DET cana-616 233 3 main main ADJ cana-616 233 4 utility utility NOUN cana-616 233 5 of of ADP cana-616 233 6 these these DET cana-616 233 7 tests test NOUN cana-616 233 8 is be AUX cana-616 233 9 to to PART cana-616 233 10 either either CCONJ cana-616 233 11 confirm confirm VERB cana-616 233 12 or or CCONJ cana-616 233 13 refute refute VERB cana-616 233 14 assumptions assumption NOUN cana-616 233 15 or or CCONJ cana-616 233 16 disease disease NOUN cana-616 233 17 spread spread VERB cana-616 233 18 , , PUNCT cana-616 233 19 along along ADP cana-616 233 20 with with ADP cana-616 233 21 those those PRON cana-616 233 22 which which PRON cana-616 233 23 can can AUX cana-616 233 24 be be AUX cana-616 233 25 considered consider VERB cana-616 233 26 to to PART cana-616 233 27 be be AUX cana-616 233 28 its its PRON cana-616 233 29 main main ADJ cana-616 233 30 factors factor NOUN cana-616 233 31 of of ADP cana-616 233 32 risk risk NOUN cana-616 233 33 . . PUNCT cana-616 234 1 with with ADP cana-616 234 2 such such ADJ cana-616 234 3 clear clear ADJ cana-616 234 4 evidence evidence NOUN cana-616 234 5 , , PUNCT cana-616 234 6 precise precise ADJ cana-616 234 7 management management NOUN cana-616 234 8 strategies strategy NOUN cana-616 234 9 are be AUX cana-616 234 10 devised devise VERB cana-616 234 11 to to PART cana-616 234 12 prohibit prohibit VERB cana-616 234 13 the the DET cana-616 234 14 spread spread NOUN cana-616 234 15 of of ADP cana-616 234 16 diseases disease NOUN cana-616 234 17 . . PUNCT cana-616 235 1 regression regression NOUN cana-616 235 2 analysis analysis NOUN cana-616 235 3 : : PUNCT cana-616 235 4 linear linear ADJ cana-616 235 5 or or CCONJ cana-616 235 6 logistic logistic ADJ cana-616 235 7 regression regression NOUN cana-616 235 8 is be AUX cana-616 235 9 applied apply VERB cana-616 235 10 to to PART cana-616 235 11 explore explore VERB cana-616 235 12 and and CCONJ cana-616 235 13 to to PART cana-616 235 14 explain explain VERB cana-616 235 15 how how SCONJ cana-616 235 16 different different ADJ cana-616 235 17 characteristics characteristic NOUN cana-616 235 18 correlate correlate VERB cana-616 235 19 with with ADP cana-616 235 20 the the DET cana-616 235 21 chance chance NOUN cana-616 235 22 for for ADP cana-616 235 23 an an DET cana-616 235 24 epidemic epidemic NOUN cana-616 235 25 . . PUNCT cana-616 236 1 these these DET cana-616 236 2 models model NOUN cana-616 236 3 generate generate VERB cana-616 236 4 accurate accurate ADJ cana-616 236 5 scenarios scenario NOUN cana-616 236 6 communications communication NOUN cana-616 236 7 on on ADP cana-616 236 8 applied apply VERB cana-616 236 9 nonlinear nonlinear ADJ cana-616 236 10 analysis analysis NOUN cana-616 236 11 issn issn NOUN cana-616 236 12 : : PUNCT cana-616 236 13 1074 1074 NUM cana-616 236 14 - - PUNCT cana-616 236 15 133x 133x NUM cana-616 236 16 vol vol NOUN cana-616 236 17 31 31 NUM cana-616 236 18 no no NOUN cana-616 236 19 . . PUNCT cana-616 237 1 2s 2s NUM cana-616 237 2 ( ( PUNCT cana-616 237 3 2024 2024 NUM cana-616 237 4 ) ) PUNCT cana-616 237 5 135 135 NUM cana-616 237 6 https://internationalpubls.com https://internationalpubls.com X cana-616 237 7 indicating indicate VERB cana-616 237 8 how how SCONJ cana-616 237 9 the the DET cana-616 237 10 precursor precursor NOUN cana-616 237 11 factors factor NOUN cana-616 237 12 , , PUNCT cana-616 237 13 like like ADP cana-616 237 14 climate climate NOUN cana-616 237 15 variables variable NOUN cana-616 237 16 , , PUNCT cana-616 237 17 animal animal NOUN cana-616 237 18 ’s ’s PART cana-616 237 19 movement movement NOUN cana-616 237 20 and and CCONJ cana-616 237 21 vaccination vaccination NOUN cana-616 237 22 rates rate NOUN cana-616 237 23 have have VERB cana-616 237 24 a a DET cana-616 237 25 leading lead VERB cana-616 237 26 role role NOUN cana-616 237 27 in in ADP cana-616 237 28 the the DET cana-616 237 29 likelihood likelihood NOUN cana-616 237 30 of of ADP cana-616 237 31 lsd lsd NOUN cana-616 237 32 being be AUX cana-616 237 33 of of ADP cana-616 237 34 occurrence occurrence NOUN cana-616 237 35 . . PUNCT cana-616 238 1 figure figure VERB cana-616 238 2 7 7 NUM cana-616 238 3 : : PUNCT cana-616 238 4 no no INTJ cana-616 238 5 . . NOUN cana-616 239 1 of of ADP cana-616 239 2 cases case NOUN cana-616 239 3 v v ADP cana-616 239 4 / / SYM cana-616 239 5 s s PART cana-616 239 6 time time NOUN cana-616 239 7 series series NOUN cana-616 239 8 of of ADP cana-616 239 9 lsd lsd NOUN cana-616 239 10 cases case NOUN cana-616 239 11 figure figure VERB cana-616 239 12 8 8 NUM cana-616 239 13 : : PUNCT cana-616 239 14 various various ADJ cana-616 239 15 parameter parameter NOUN cana-616 239 16 analysis analysis NOUN cana-616 239 17 for for ADP cana-616 239 18 lumpy lumpy ADJ cana-616 239 19 machine machine NOUN cana-616 239 20 learning learning NOUN cana-616 239 21 model model PROPN cana-616 239 22 development development PROPN cana-616 239 23 and and CCONJ cana-616 239 24 evaluation evaluation NOUN cana-616 239 25 model model NOUN cana-616 239 26 selection selection NOUN cana-616 239 27 and and CCONJ cana-616 239 28 training training NOUN cana-616 239 29 : : PUNCT cana-616 239 30 selection selection NOUN cana-616 239 31 of of ADP cana-616 239 32 proper proper ADJ cana-616 239 33 machine machine NOUN cana-616 239 34 learning learning NOUN cana-616 239 35 algorithms algorithm NOUN cana-616 239 36 , , PUNCT cana-616 239 37 encompassing encompass VERB cana-616 239 38 models model NOUN cana-616 239 39 from from ADP cana-616 239 40 the the DET cana-616 239 41 logistic logistic ADJ cana-616 239 42 regression regression NOUN cana-616 239 43 as as ADP cana-616 239 44 the the DET cana-616 239 45 simplest simple ADJ cana-616 239 46 one one NOUN cana-616 239 47 to to PART cana-616 239 48 ensemble ensemble VERB cana-616 239 49 methods method NOUN cana-616 239 50 such such ADJ cana-616 239 51 as as ADP cana-616 239 52 random random ADJ cana-616 239 53 forests forest NOUN cana-616 239 54 and and CCONJ cana-616 239 55 gradient gradient ADJ cana-616 239 56 boosting boost VERB cana-616 239 57 machines machine NOUN cana-616 239 58 , , PUNCT cana-616 239 59 is be AUX cana-616 239 60 contingent contingent ADJ cana-616 239 61 upon upon SCONJ cana-616 239 62 the the DET cana-616 239 63 nature nature NOUN cana-616 239 64 of of ADP cana-616 239 65 the the DET cana-616 239 66 dataset dataset NOUN cana-616 239 67 and and CCONJ cana-616 240 1 the the DET cana-616 240 2 particular particular ADJ cana-616 240 3 objectives objective NOUN cana-616 240 4 communications communication NOUN cana-616 240 5 on on ADP cana-616 240 6 applied apply VERB cana-616 240 7 nonlinear nonlinear ADJ cana-616 240 8 analysis analysis NOUN cana-616 240 9 issn issn NOUN cana-616 240 10 : : PUNCT cana-616 240 11 1074 1074 NUM cana-616 240 12 - - PUNCT cana-616 240 13 133x 133x NUM cana-616 240 14 vol vol NOUN cana-616 240 15 31 31 NUM cana-616 240 16 no no NOUN cana-616 240 17 . . PUNCT cana-616 241 1 2s 2s NUM cana-616 241 2 ( ( PUNCT cana-616 241 3 2024 2024 NUM cana-616 241 4 ) ) PUNCT cana-616 241 5 136 136 NUM cana-616 241 6 https://internationalpubls.com https://internationalpubls.com X cana-616 241 7 of of ADP cana-616 241 8 the the DET cana-616 241 9 analysis analysis NOUN cana-616 241 10 . . PUNCT cana-616 242 1 parameter parameter NOUN cana-616 242 2 tuning tuning NOUN cana-616 242 3 is be AUX cana-616 242 4 trained train VERB cana-616 242 5 throughout throughout ADP cana-616 242 6 the the DET cana-616 242 7 process process NOUN cana-616 242 8 to to PART cana-616 242 9 increase increase VERB cana-616 242 10 model model NOUN cana-616 242 11 accuracy accuracy NOUN cana-616 242 12 and and CCONJ cana-616 242 13 reduce reduce VERB cana-616 242 14 furthering further VERB cana-616 242 15 . . PUNCT cana-616 243 1 strategies strategy NOUN cana-616 243 2 like like ADP cana-616 243 3 cross cross NOUN cana-616 243 4 - - ADJ cana-616 243 5 validation validation NOUN cana-616 243 6 are be AUX cana-616 243 7 used use VERB cana-616 243 8 in in ADP cana-616 243 9 the the DET cana-616 243 10 process process NOUN cana-616 243 11 . . PUNCT cana-616 244 1 figure figure VERB cana-616 244 2 9 9 NUM cana-616 244 3 : : PUNCT cana-616 244 4 cattel cattel NOUN cana-616 244 5 density density PROPN cana-616 244 6 v v PROPN cana-616 244 7 / / SYM cana-616 244 8 s s NOUN cana-616 244 9 lsd lsd NOUN cana-616 244 10 cases case NOUN cana-616 244 11 total total ADJ cana-616 244 12 lsd lsd NOUN cana-616 244 13 cases case NOUN cana-616 244 14 by by ADP cana-616 244 15 region region NOUN cana-616 244 16 : : PUNCT cana-616 244 17 total total ADJ cana-616 244 18 lsd lsd NOUN cana-616 244 19 cases case NOUN cana-616 244 20 by by ADP cana-616 244 21 region region NOUN cana-616 244 22 : : PUNCT cana-616 244 23 here here ADV cana-616 244 24 is be AUX cana-616 244 25 an an DET cana-616 244 26 embodiment embodiment NOUN cana-616 244 27 of of ADP cana-616 244 28 the the DET cana-616 244 29 statistics statistic NOUN cana-616 244 30 of of ADP cana-616 244 31 reported report VERB cana-616 244 32 lsd lsd NOUN cana-616 244 33 cases case NOUN cana-616 244 34 within within ADP cana-616 244 35 different different ADJ cana-616 244 36 areas area NOUN cana-616 244 37 . . PUNCT cana-616 245 1 it it PRON cana-616 245 2 is be AUX cana-616 245 3 essential essential ADJ cana-616 245 4 for for ADP cana-616 245 5 both both DET cana-616 245 6 identification identification NOUN cana-616 245 7 of of ADP cana-616 245 8 the the DET cana-616 245 9 areas area NOUN cana-616 245 10 with with ADP cana-616 245 11 higher high ADJ cana-616 245 12 levels level NOUN cana-616 245 13 of of ADP cana-616 245 14 diseases disease NOUN cana-616 245 15 and and CCONJ cana-616 245 16 focusing focus VERB cana-616 245 17 on on ADP cana-616 245 18 such such ADJ cana-616 245 19 sectors sector NOUN cana-616 245 20 for for ADP cana-616 245 21 conducting conduct VERB cana-616 245 22 further further ADJ cana-616 245 23 epidemiological epidemiological ADJ cana-616 245 24 research research NOUN cana-616 245 25 and and CCONJ cana-616 245 26 targeted target VERB cana-616 245 27 interventions intervention NOUN cana-616 245 28 . . PUNCT cana-616 246 1 correlation correlation NOUN cana-616 246 2 heatmap heatmap NOUN cana-616 246 3 of of ADP cana-616 246 4 climatic climatic ADJ cana-616 246 5 variables variable NOUN cana-616 246 6 with with ADP cana-616 246 7 lsd lsd NOUN cana-616 246 8 cases case NOUN cana-616 246 9 : : PUNCT cana-616 246 10 correlation correlation NOUN cana-616 246 11 heatmap heatmap NOUN cana-616 246 12 of of ADP cana-616 246 13 climatic climatic ADJ cana-616 246 14 variables variable NOUN cana-616 246 15 with with ADP cana-616 246 16 lsd lsd NOUN cana-616 246 17 cases case NOUN cana-616 246 18 : : PUNCT cana-616 246 19 the the DET cana-616 246 20 heatmap heatmap NOUN cana-616 246 21 exemplifies exemplify VERB cana-616 246 22 linkage linkage NOUN cana-616 246 23 between between ADP cana-616 246 24 the the DET cana-616 246 25 climatic climatic ADJ cana-616 246 26 variables variable NOUN cana-616 246 27 as as ADV cana-616 246 28 well well ADV cana-616 246 29 as as ADP cana-616 246 30 their their PRON cana-616 246 31 association association NOUN cana-616 246 32 with with ADP cana-616 246 33 the the DET cana-616 246 34 incidence incidence NOUN cana-616 246 35 of of ADP cana-616 246 36 lsd lsd NOUN cana-616 246 37 . . PUNCT cana-616 247 1 identification identification NOUN cana-616 247 2 of of ADP cana-616 247 3 the the DET cana-616 247 4 surrounding surround VERB cana-616 247 5 environmental environmental ADJ cana-616 247 6 elements element NOUN cana-616 247 7 that that PRON cana-616 247 8 may may AUX cana-616 247 9 have have VERB cana-616 247 10 an an DET cana-616 247 11 effect effect NOUN cana-616 247 12 on on ADP cana-616 247 13 precipitation precipitation NOUN cana-616 247 14 and and CCONJ cana-616 247 15 high high ADJ cana-616 247 16 temperature temperature NOUN cana-616 247 17 together together ADV cana-616 247 18 with with ADP cana-616 247 19 humidity humidity NOUN cana-616 247 20 is be AUX cana-616 247 21 critical critical ADJ cana-616 247 22 . . PUNCT cana-616 248 1 time time NOUN cana-616 248 2 series series PROPN cana-616 248 3 of of ADP cana-616 248 4 lsd lsd NOUN cana-616 248 5 cases case NOUN cana-616 248 6 : : PUNCT cana-616 248 7 time time NOUN cana-616 248 8 series series PROPN cana-616 248 9 of of ADP cana-616 248 10 lsd lsd NOUN cana-616 248 11 cases case NOUN cana-616 248 12 : : PUNCT cana-616 248 13 the the DET cana-616 248 14 time time NOUN cana-616 248 15 series series PROPN cana-616 248 16 chart chart NOUN cana-616 248 17 is be AUX cana-616 248 18 given give VERB cana-616 248 19 to to PART cana-616 248 20 show show VERB cana-616 248 21 the the DET cana-616 248 22 number number NOUN cana-616 248 23 of of ADP cana-616 248 24 cases case NOUN cana-616 248 25 reported report VERB cana-616 248 26 due due ADP cana-616 248 27 to to ADP cana-616 248 28 lsd lsd PROPN cana-616 248 29 observed observe VERB cana-616 248 30 over over ADP cana-616 248 31 time time NOUN cana-616 248 32 which which PRON cana-616 248 33 gives give VERB cana-616 248 34 ideas idea NOUN cana-616 248 35 about about ADP cana-616 248 36 the the DET cana-616 248 37 cycles cycle NOUN cana-616 248 38 or or CCONJ cana-616 248 39 seasonality seasonality NOUN cana-616 248 40 and and CCONJ cana-616 248 41 spikes spike NOUN cana-616 248 42 . . PUNCT cana-616 249 1 that that DET cana-616 249 2 type type NOUN cana-616 249 3 of of ADP cana-616 249 4 time time NOUN cana-616 249 5 investigations investigation NOUN cana-616 249 6 is be AUX cana-616 249 7 very very ADV cana-616 249 8 important important ADJ cana-616 249 9 for for ADP cana-616 249 10 deciding decide VERB cana-616 249 11 preventive preventive ADJ cana-616 249 12 steps step NOUN cana-616 249 13 and and CCONJ cana-616 249 14 knowing know VERB cana-616 249 15 what what DET cana-616 249 16 type type NOUN cana-616 249 17 of of ADP cana-616 249 18 cyclic cyclic ADJ cana-616 249 19 nature nature NOUN cana-616 249 20 may may AUX cana-616 249 21 be be AUX cana-616 249 22 the the DET cana-616 249 23 case case NOUN cana-616 249 24 , , PUNCT cana-616 249 25 if if SCONJ cana-616 249 26 there there PRON cana-616 249 27 is be VERB cana-616 249 28 one one NUM cana-616 249 29 . . PUNCT cana-616 250 1 comparison comparison NOUN cana-616 250 2 of of ADP cana-616 250 3 climatic climatic ADJ cana-616 250 4 conditions condition NOUN cana-616 250 5 by by ADP cana-616 250 6 lsd lsd NOUN cana-616 250 7 presence presence NOUN cana-616 250 8 : : PUNCT cana-616 250 9 comparison comparison NOUN cana-616 250 10 of of ADP cana-616 250 11 climatic climatic ADJ cana-616 250 12 conditions condition NOUN cana-616 250 13 by by ADP cana-616 250 14 lsd lsd NOUN cana-616 250 15 presence presence NOUN cana-616 250 16 : : PUNCT cana-616 250 17 besides besides ADV cana-616 250 18 , , PUNCT cana-616 250 19 these these DET cana-616 250 20 boxplots boxplot NOUN cana-616 250 21 show show VERB cana-616 250 22 the the DET cana-616 250 23 data datum NOUN cana-616 250 24 of of ADP cana-616 250 25 temperature temperature NOUN cana-616 250 26 means mean NOUN cana-616 250 27 , , PUNCT cana-616 250 28 precipitation precipitation NOUN cana-616 250 29 amount amount NOUN cana-616 250 30 , , PUNCT cana-616 250 31 diurnal diurnal ADJ cana-616 250 32 temperature temperature NOUN cana-616 250 33 range range NOUN cana-616 250 34 , , PUNCT cana-616 250 35 and and CCONJ cana-616 250 36 vapor vapor NOUN cana-616 250 37 pressure pressure NOUN cana-616 250 38 in in ADP cana-616 250 39 two two NUM cana-616 250 40 groups group NOUN cana-616 250 41 that that PRON cana-616 250 42 have have VERB cana-616 250 43 lsd lsd NOUN cana-616 250 44 outbreaks outbreak NOUN cana-616 250 45 and and CCONJ cana-616 250 46 those those PRON cana-616 250 47 without without ADP cana-616 250 48 such such ADJ cana-616 250 49 outbreaks outbreak NOUN cana-616 250 50 . . PUNCT cana-616 251 1 climatic climatic ADJ cana-616 251 2 evidence evidence NOUN cana-616 251 3 was be AUX cana-616 251 4 seen see VERB cana-616 251 5 in in ADP cana-616 251 6 the the DET cana-616 251 7 varied varied ADJ cana-616 251 8 outbreaks outbreak NOUN cana-616 251 9 and and CCONJ cana-616 251 10 their their PRON cana-616 251 11 locations location NOUN cana-616 251 12 when when SCONJ cana-616 251 13 no no DET cana-616 251 14 discernible discernible ADJ cana-616 251 15 succession succession NOUN cana-616 251 16 or or CCONJ cana-616 251 17 cause cause NOUN cana-616 251 18 explained explain VERB cana-616 251 19 these these DET cana-616 251 20 differences difference NOUN cana-616 251 21 . . PUNCT cana-616 252 1 communications communication NOUN cana-616 252 2 on on ADP cana-616 252 3 applied apply VERB cana-616 252 4 nonlinear nonlinear ADJ cana-616 252 5 analysis analysis NOUN cana-616 252 6 issn issn NOUN cana-616 252 7 : : PUNCT cana-616 252 8 1074 1074 NUM cana-616 252 9 - - PUNCT cana-616 252 10 133x 133x NUM cana-616 252 11 vol vol NOUN cana-616 252 12 31 31 NUM cana-616 252 13 no no NOUN cana-616 252 14 . . PUNCT cana-616 253 1 2s 2s NUM cana-616 253 2 ( ( PUNCT cana-616 253 3 2024 2024 NUM cana-616 253 4 ) ) PUNCT cana-616 253 5 137 137 NUM cana-616 253 6 https://internationalpubls.com https://internationalpubls.com X cana-616 253 7 the the DET cana-616 253 8 scatter scatter NOUN cana-616 253 9 plot plot NOUN cana-616 253 10 serves serve VERB cana-616 253 11 the the DET cana-616 253 12 topic topic NOUN cana-616 253 13 of of ADP cana-616 253 14 the the DET cana-616 253 15 correlation correlation NOUN cana-616 253 16 between between ADP cana-616 253 17 cattle cattle NOUN cana-616 253 18 density density NOUN cana-616 253 19 and and CCONJ cana-616 253 20 the the DET cana-616 253 21 frequency frequency NOUN cana-616 253 22 of of ADP cana-616 253 23 lsd lsd NOUN cana-616 253 24 . . PUNCT cana-616 254 1 this this DET cana-616 254 2 image image NOUN cana-616 254 3 may may AUX cana-616 254 4 do do VERB cana-616 254 5 a a DET cana-616 254 6 good good ADJ cana-616 254 7 job job NOUN cana-616 254 8 to to PART cana-616 254 9 assume assume VERB cana-616 254 10 that that SCONJ cana-616 254 11 intense intense ADJ cana-616 254 12 animal animal NOUN cana-616 254 13 concentration concentration NOUN cana-616 254 14 requires require VERB cana-616 254 15 proximity proximity NOUN cana-616 254 16 for for ADP cana-616 254 17 animal animal NOUN cana-616 254 18 ’s ’s PART cana-616 254 19 connection connection NOUN cana-616 254 20 that that PRON cana-616 254 21 then then ADV cana-616 254 22 can can AUX cana-616 254 23 increase increase VERB cana-616 254 24 the the DET cana-616 254 25 disease disease NOUN cana-616 254 26 spreading spread VERB cana-616 254 27 opportunities opportunity NOUN cana-616 254 28 . . PUNCT cana-616 255 1 grouping group VERB cana-616 255 2 of of ADP cana-616 255 3 all all DET cana-616 255 4 the the DET cana-616 255 5 abovementioned abovementione VERB cana-616 255 6 visualizations visualization NOUN cana-616 255 7 in in ADP cana-616 255 8 such such ADJ cana-616 255 9 way way NOUN cana-616 255 10 assists assist VERB cana-616 255 11 simultaneously simultaneously ADV cana-616 255 12 in in ADP cana-616 255 13 the the DET cana-616 255 14 epidemiology epidemiology NOUN cana-616 255 15 comprehension comprehension NOUN cana-616 255 16 of of ADP cana-616 255 17 the the DET cana-616 255 18 lumpy lumpy ADJ cana-616 255 19 skin skin NOUN cana-616 255 20 disease disease NOUN cana-616 255 21 and and CCONJ cana-616 255 22 the the DET cana-616 255 23 designing designing NOUN cana-616 255 24 of of ADP cana-616 255 25 the the DET cana-616 255 26 most most ADV cana-616 255 27 meaningful meaningful ADJ cana-616 255 28 control control NOUN cana-616 255 29 strategies strategy NOUN cana-616 255 30 . . PUNCT cana-616 256 1 figure figure NOUN cana-616 256 2 10 10 NUM cana-616 256 3 : : PUNCT cana-616 256 4 comprehensive comprehensive ADJ cana-616 256 5 overview overview NOUN cana-616 256 6 of of ADP cana-616 256 7 the the DET cana-616 256 8 factors factor NOUN cana-616 256 9 associated associate VERB cana-616 256 10 with with ADP cana-616 256 11 lumpy lumpy ADJ cana-616 256 12 skin skin NOUN cana-616 256 13 disease disease NOUN cana-616 256 14 model model NOUN cana-616 256 15 evaluation evaluation NOUN cana-616 256 16 : : PUNCT cana-616 256 17 one one NUM cana-616 256 18 of of ADP cana-616 256 19 the the DET cana-616 256 20 key key ADJ cana-616 256 21 evaluation evaluation NOUN cana-616 256 22 steps step NOUN cana-616 256 23 is be AUX cana-616 256 24 to to PART cana-616 256 25 assess assess VERB cana-616 256 26 the the DET cana-616 256 27 model model NOUN cana-616 256 28 performance performance NOUN cana-616 256 29 with with ADP cana-616 256 30 a a DET cana-616 256 31 set set NOUN cana-616 256 32 of of ADP cana-616 256 33 metrics metric NOUN cana-616 256 34 comprising comprising NOUN cana-616 256 35 accuracy accuracy NOUN cana-616 256 36 , , PUNCT cana-616 256 37 precision precision NOUN cana-616 256 38 , , PUNCT cana-616 256 39 recall recall NOUN cana-616 256 40 , , PUNCT cana-616 256 41 f1 f1 NOUN cana-616 256 42 - - PUNCT cana-616 256 43 score score NOUN cana-616 256 44 , , PUNCT cana-616 256 45 and and CCONJ cana-616 256 46 roc roc NOUN cana-616 256 47 - - PUNCT cana-616 256 48 auc auc NOUN cana-616 256 49 scores score NOUN cana-616 256 50 . . PUNCT cana-616 257 1 these these DET cana-616 257 2 metrics metric NOUN cana-616 257 3 are be AUX cana-616 257 4 not not PART cana-616 257 5 only only ADV cana-616 257 6 aimed aim VERB cana-616 257 7 at at ADP cana-616 257 8 determining determine VERB cana-616 257 9 the the DET cana-616 257 10 model model NOUN cana-616 257 11 ’s ’s PART cana-616 257 12 specificity specificity NOUN cana-616 257 13 in in ADP cana-616 257 14 real real ADJ cana-616 257 15 lsd lsd NOUN cana-616 257 16 cases case NOUN cana-616 257 17 but but CCONJ cana-616 257 18 also also ADV cana-616 257 19 evaluate evaluate VERB cana-616 257 20 it it PRON cana-616 257 21 based base VERB cana-616 257 22 on on ADP cana-616 257 23 how how SCONJ cana-616 257 24 it it PRON cana-616 257 25 reduces reduce VERB cana-616 257 26 the the DET cana-616 257 27 false false ADJ cana-616 257 28 alarms alarm NOUN cana-616 257 29 . . PUNCT cana-616 258 1 lectures lecture NOUN cana-616 258 2 and and CCONJ cana-616 258 3 seminars seminar NOUN cana-616 258 4 usually usually ADV cana-616 258 5 include include VERB cana-616 258 6 performances performance NOUN cana-616 258 7 demonstrating demonstrate VERB cana-616 258 8 this this DET cana-616 258 9 model model NOUN cana-616 258 10 as as ADP cana-616 258 11 practical practical ADJ cana-616 258 12 . . PUNCT cana-616 259 1 feature feature NOUN cana-616 259 2 importance importance NOUN cana-616 259 3 and and CCONJ cana-616 259 4 model model NOUN cana-616 259 5 interpretation interpretation NOUN cana-616 259 6 : : PUNCT cana-616 259 7 in in ADP cana-616 259 8 the the DET cana-616 259 9 process process NOUN cana-616 259 10 , , PUNCT cana-616 259 11 it it PRON cana-616 259 12 may may AUX cana-616 259 13 become become VERB cana-616 259 14 more more ADV cana-616 259 15 obvious obvious ADJ cana-616 259 16 to to PART cana-616 259 17 see see VERB cana-616 259 18 what what PRON cana-616 259 19 attributes attribute NOUN cana-616 259 20 are be AUX cana-616 259 21 important important ADJ cana-616 259 22 in in ADP cana-616 259 23 the the DET cana-616 259 24 predictions prediction NOUN cana-616 259 25 that that PRON cana-616 259 26 the the DET cana-616 259 27 model model NOUN cana-616 259 28 makes make VERB cana-616 259 29 . . PUNCT cana-616 260 1 feature feature NOUN cana-616 260 2 score score NOUN cana-616 260 3 ranking rank VERB cana-616 260 4 awards award NOUN cana-616 260 5 the the DET cana-616 260 6 top top ADJ cana-616 260 7 priority priority NOUN cana-616 260 8 to to ADP cana-616 260 9 the the DET cana-616 260 10 variables variable NOUN cana-616 260 11 that that PRON cana-616 260 12 are be AUX cana-616 260 13 the the DET cana-616 260 14 most most ADV cana-616 260 15 capable capable ADJ cana-616 260 16 of of ADP cana-616 260 17 predicting predict VERB cana-616 260 18 the the DET cana-616 260 19 outcomes outcome NOUN cana-616 260 20 of of ADP cana-616 260 21 the the DET cana-616 260 22 prevention prevention NOUN cana-616 260 23 and and CCONJ cana-616 260 24 as as ADV cana-616 260 25 well well ADV cana-616 260 26 of of ADP cana-616 260 27 the the DET cana-616 260 28 targeted target VERB cana-616 260 29 treatment treatment NOUN cana-616 260 30 intervention intervention NOUN cana-616 260 31 . . PUNCT cana-616 261 1 the the DET cana-616 261 2 other other ADJ cana-616 261 3 factor factor NOUN cana-616 261 4 that that PRON cana-616 261 5 underscores underscore VERB cana-616 261 6 model model NOUN cana-616 261 7 interpretability interpretability NOUN cana-616 261 8 , , PUNCT cana-616 261 9 communications communication NOUN cana-616 261 10 on on ADP cana-616 261 11 applied apply VERB cana-616 261 12 nonlinear nonlinear ADJ cana-616 261 13 analysis analysis NOUN cana-616 261 14 issn issn NOUN cana-616 261 15 : : PUNCT cana-616 261 16 1074 1074 NUM cana-616 261 17 - - PUNCT cana-616 261 18 133x 133x NUM cana-616 261 19 vol vol NOUN cana-616 261 20 31 31 NUM cana-616 261 21 no no NOUN cana-616 261 22 . . PUNCT cana-616 262 1 2s 2s NUM cana-616 262 2 ( ( PUNCT cana-616 262 3 2024 2024 NUM cana-616 262 4 ) ) PUNCT cana-616 262 5 138 138 NUM cana-616 262 6 https://internationalpubls.com https://internationalpubls.com X cana-616 262 7 especially especially ADV cana-616 262 8 for for ADP cana-616 262 9 complicated complicated ADJ cana-616 262 10 models model NOUN cana-616 262 11 , , PUNCT cana-616 262 12 is be AUX cana-616 262 13 comprehensibility comprehensibility NOUN cana-616 262 14 in in ADP cana-616 262 15 order order NOUN cana-616 262 16 to to PART cana-616 262 17 aid aid VERB cana-616 262 18 the the DET cana-616 262 19 stakeholders stakeholder NOUN cana-616 262 20 comprehend comprehend VERB cana-616 262 21 and and CCONJ cana-616 262 22 trust trust VERB cana-616 262 23 the the DET cana-616 262 24 recommendations recommendation NOUN cana-616 262 25 given give VERB cana-616 262 26 by by ADP cana-616 262 27 the the DET cana-616 262 28 model model NOUN cana-616 262 29 . . PUNCT cana-616 263 1 figure figure VERB cana-616 263 2 11 11 NUM cana-616 263 3 : : PUNCT cana-616 263 4 region region NOUN cana-616 263 5 wise wise ADJ cana-616 263 6 percentage percentage NOUN cana-616 263 7 spread spread NOUN cana-616 263 8 of of ADP cana-616 263 9 lsd lsd NOUN cana-616 263 10 figure figure NOUN cana-616 263 11 12 12 NUM cana-616 263 12 : : PUNCT cana-616 263 13 dd dd VERB cana-616 263 14 detection detection NOUN cana-616 263 15 v v ADP cana-616 263 16 / / SYM cana-616 263 17 s s NOUN cana-616 263 18 density density NOUN cana-616 263 19 communications communication NOUN cana-616 263 20 on on ADP cana-616 263 21 applied apply VERB cana-616 263 22 nonlinear nonlinear ADJ cana-616 263 23 analysis analysis NOUN cana-616 263 24 issn issn NOUN cana-616 263 25 : : PUNCT cana-616 263 26 1074 1074 NUM cana-616 263 27 - - PUNCT cana-616 263 28 133x 133x NUM cana-616 263 29 vol vol NOUN cana-616 263 30 31 31 NUM cana-616 263 31 no no NOUN cana-616 263 32 . . PUNCT cana-616 264 1 2s 2s NUM cana-616 264 2 ( ( PUNCT cana-616 264 3 2024 2024 NUM cana-616 264 4 ) ) PUNCT cana-616 264 5 139 139 NUM cana-616 264 6 https://internationalpubls.com https://internationalpubls.com X cana-616 264 7 figure figure NOUN cana-616 264 8 13 13 NUM cana-616 264 9 : : PUNCT cana-616 264 10 density density NOUN cana-616 264 11 v v PROPN cana-616 264 12 / / SYM cana-616 264 13 s s PART cana-616 264 14 diurnal diurnal ADJ cana-616 264 15 temperature temperature NOUN cana-616 264 16 range range NOUN cana-616 264 17 in in ADP cana-616 264 18 degrees degree NOUN cana-616 264 19 ( ( PUNCT cana-616 264 20 dtr dtr NOUN cana-616 264 21 ) ) PUNCT cana-616 264 22 figure figure NOUN cana-616 264 23 14 14 NUM cana-616 264 24 : : PUNCT cana-616 264 25 model model PROPN cana-616 264 26 accuracy accuracy NOUN cana-616 264 27 comparison comparison NOUN cana-616 264 28 figure figure NOUN cana-616 264 29 15 15 NUM cana-616 264 30 : : PUNCT cana-616 264 31 precision precision NOUN cana-616 264 32 , , PUNCT cana-616 264 33 recall recall NOUN cana-616 264 34 and and CCONJ cana-616 264 35 f1 f1 PROPN cana-616 264 36 score score NOUN cana-616 264 37 v v NOUN cana-616 264 38 / / SYM cana-616 264 39 s s NOUN cana-616 264 40 value value NOUN cana-616 264 41 communications communication NOUN cana-616 264 42 on on ADP cana-616 264 43 applied apply VERB cana-616 264 44 nonlinear nonlinear ADJ cana-616 264 45 analysis analysis NOUN cana-616 264 46 issn issn NOUN cana-616 264 47 : : PUNCT cana-616 264 48 1074 1074 NUM cana-616 264 49 - - PUNCT cana-616 264 50 133x 133x NUM cana-616 264 51 vol vol NOUN cana-616 264 52 31 31 NUM cana-616 264 53 no no NOUN cana-616 264 54 . . PUNCT cana-616 265 1 2s 2s NUM cana-616 265 2 ( ( PUNCT cana-616 265 3 2024 2024 NUM cana-616 265 4 ) ) PUNCT cana-616 265 5 140 140 NUM cana-616 265 6 https://internationalpubls.com https://internationalpubls.com X cana-616 265 7 figure figure NOUN cana-616 265 8 16 16 NUM cana-616 265 9 : : PUNCT cana-616 265 10 analysis analysis NOUN cana-616 265 11 of of ADP cana-616 265 12 learning learn VERB cana-616 265 13 rate rate NOUN cana-616 265 14 and and CCONJ cana-616 265 15 model model NOUN cana-616 265 16 error error NOUN cana-616 265 17 dynamics dynamic NOUN cana-616 265 18 information information NOUN cana-616 265 19 provided provide VERB cana-616 265 20 was be AUX cana-616 265 21 the the DET cana-616 265 22 observations observation NOUN cana-616 265 23 performed perform VERB cana-616 265 24 on on ADP cana-616 265 25 different different ADJ cana-616 265 26 climatic climatic ADJ cana-616 265 27 and and CCONJ cana-616 265 28 geographic geographic ADJ cana-616 265 29 qualities quality NOUN cana-616 265 30 that that PRON cana-616 265 31 were be AUX cana-616 265 32 distributed distribute VERB cana-616 265 33 in in ADP cana-616 265 34 different different ADJ cana-616 265 35 locations location NOUN cana-616 265 36 with with ADP cana-616 265 37 natives native NOUN cana-616 265 38 as as ADP cana-616 265 39 the the DET cana-616 265 40 main main ADJ cana-616 265 41 source source NOUN cana-616 265 42 of of ADP cana-616 265 43 information information NOUN cana-616 265 44 . . PUNCT cana-616 265 45 " " PUNCT cana-616 266 1 perhaps perhaps ADV cana-616 266 2 the the DET cana-616 266 3 most most ADV cana-616 266 4 essential essential ADJ cana-616 266 5 thing thing NOUN cana-616 266 6 concerning concern VERB cana-616 266 7 our our PRON cana-616 266 8 model model NOUN cana-616 266 9 was be AUX cana-616 266 10 that that SCONJ cana-616 266 11 the the DET cana-616 266 12 " " PUNCT cana-616 266 13 lumpiness lumpiness NOUN cana-616 266 14 " " PUNCT cana-616 266 15 being be AUX cana-616 266 16 true true ADJ cana-616 266 17 case case NOUN cana-616 266 18 and and CCONJ cana-616 266 19 the the DET cana-616 266 20 " " PUNCT cana-616 266 21 lumpiness lumpiness NOUN cana-616 266 22 " " PUNCT cana-616 266 23 being be AUX cana-616 266 24 false false ADJ cana-616 266 25 case case NOUN cana-616 266 26 were be AUX cana-616 266 27 in in ADP cana-616 266 28 the the DET cana-616 266 29 state state NOUN cana-616 266 30 of of ADP cana-616 266 31 imbalance imbalance NOUN cana-616 266 32 . . PUNCT cana-616 267 1 a a DET cana-616 267 2 skewed skewed ADJ cana-616 267 3 dataset dataset NOUN cana-616 267 4 of of ADP cana-616 267 5 class class NOUN cana-616 267 6 distribution distribution NOUN cana-616 267 7 will will AUX cana-616 267 8 lead lead VERB cana-616 267 9 to to ADP cana-616 267 10 skewed skewed ADJ cana-616 267 11 prediction prediction NOUN cana-616 267 12 , , PUNCT cana-616 267 13 where where SCONJ cana-616 267 14 the the DET cana-616 267 15 majority majority NOUN cana-616 267 16 class class NOUN cana-616 267 17 will will AUX cana-616 267 18 be be AUX cana-616 267 19 favored favor VERB cana-616 267 20 . . PUNCT cana-616 268 1 data datum NOUN cana-616 268 2 preprocessing preprocessing NOUN cana-616 268 3 and and CCONJ cana-616 268 4 smote smote ADJ cana-616 268 5 implementation implementation NOUN cana-616 268 6 . . PUNCT cana-616 269 1 synthetic synthetic ADJ cana-616 269 2 minority minority NOUN cana-616 269 3 over over ADP cana-616 269 4 - - PUNCT cana-616 269 5 sampling sample VERB cana-616 269 6 technique technique NOUN cana-616 269 7 ( ( PUNCT cana-616 269 8 smote smote NOUN cana-616 269 9 ) ) PUNCT cana-616 269 10 was be AUX cana-616 269 11 used use VERB cana-616 269 12 to to PART cana-616 269 13 address address VERB cana-616 269 14 this this DET cana-616 269 15 inequality inequality NOUN cana-616 269 16 . . PUNCT cana-616 270 1 in in ADP cana-616 270 2 this this DET cana-616 270 3 regard regard NOUN cana-616 270 4 , , PUNCT cana-616 270 5 minority minority NOUN cana-616 270 6 class class NOUN cana-616 270 7 is be AUX cana-616 270 8 more more ADV cana-616 270 9 or or CCONJ cana-616 270 10 less less ADV cana-616 270 11 enlarged enlarge VERB cana-616 270 12 because because SCONJ cana-616 270 13 synthesized synthesize VERB cana-616 270 14 ones one NOUN cana-616 270 15 are be AUX cana-616 270 16 generated generate VERB cana-616 270 17 as as ADP cana-616 270 18 a a DET cana-616 270 19 result result NOUN cana-616 270 20 , , PUNCT cana-616 270 21 instead instead ADV cana-616 270 22 of of ADP cana-616 270 23 over over ADV cana-616 270 24 - - PUNCT cana-616 270 25 sampling sampling NOUN cana-616 270 26 which which PRON cana-616 270 27 is be AUX cana-616 270 28 rather rather ADV cana-616 270 29 prone prone ADJ cana-616 270 30 to to ADP cana-616 270 31 overfitting overfitte VERB cana-616 270 32 the the DET cana-616 270 33 algorithm algorithm NOUN cana-616 270 34 . . PUNCT cana-616 271 1 the the DET cana-616 271 2 other other ADJ cana-616 271 3 major major ADJ cana-616 271 4 task task NOUN cana-616 271 5 is be AUX cana-616 271 6 also also ADV cana-616 271 7 the the DET cana-616 271 8 splitting splitting NOUN cana-616 271 9 of of ADP cana-616 271 10 the the DET cana-616 271 11 set set NOUN cana-616 271 12 of of ADP cana-616 271 13 data datum NOUN cana-616 271 14 into into ADP cana-616 271 15 the the DET cana-616 271 16 training training NOUN cana-616 271 17 and and CCONJ cana-616 271 18 testing testing NOUN cana-616 271 19 sets set NOUN cana-616 271 20 for for ADP cana-616 271 21 the the DET cana-616 271 22 determination determination NOUN cana-616 271 23 of of ADP cana-616 271 24 the the DET cana-616 271 25 performance performance NOUN cana-616 271 26 of of ADP cana-616 271 27 the the DET cana-616 271 28 model model NOUN cana-616 271 29 on on ADP cana-616 271 30 the the DET cana-616 271 31 unseen unseen ADJ cana-616 271 32 data datum NOUN cana-616 271 33 , , PUNCT cana-616 271 34 which which PRON cana-616 271 35 is be AUX cana-616 271 36 also also ADV cana-616 271 37 more more ADV cana-616 271 38 reliable reliable ADJ cana-616 271 39 in in ADP cana-616 271 40 the the DET cana-616 271 41 measurement measurement NOUN cana-616 271 42 of of ADP cana-616 271 43 its its PRON cana-616 271 44 forecasting forecasting NOUN cana-616 271 45 power power NOUN cana-616 271 46 . . PUNCT cana-616 272 1 a a DET cana-616 272 2 number number NOUN cana-616 272 3 of of ADP cana-616 272 4 different different ADJ cana-616 272 5 models model NOUN cana-616 272 6 were be AUX cana-616 272 7 deployed deploy VERB cana-616 272 8 among among ADP cana-616 272 9 which which PRON cana-616 272 10 were be AUX cana-616 272 11 logistic logistic ADJ cana-616 272 12 regression regression NOUN cana-616 272 13 , , PUNCT cana-616 272 14 kneighbors kneighbor NOUN cana-616 272 15 classifier classifier NOUN cana-616 272 16 , , PUNCT cana-616 272 17 gaussian gaussian PROPN cana-616 272 18 nb nb PROPN cana-616 272 19 , , PUNCT cana-616 272 20 decision decision NOUN cana-616 272 21 tree tree NOUN cana-616 272 22 classifier classifier NOUN cana-616 272 23 , , PUNCT cana-616 272 24 and and CCONJ cana-616 272 25 random random ADJ cana-616 272 26 forest forest NOUN cana-616 272 27 classifier classifier NOUN cana-616 272 28 together together ADV cana-616 272 29 . . PUNCT cana-616 273 1 each each DET cana-616 273 2 model model NOUN cana-616 273 3 was be AUX cana-616 273 4 evaluated evaluate VERB cana-616 273 5 based base VERB cana-616 273 6 on on ADP cana-616 273 7 standard standard ADJ cana-616 273 8 performance performance NOUN cana-616 273 9 metrics metric NOUN cana-616 273 10 : : PUNCT cana-616 273 11 agreement agreement NOUN cana-616 273 12 , , PUNCT cana-616 273 13 specificity specificity NOUN cana-616 273 14 , , PUNCT cana-616 273 15 accuracy accuracy NOUN cana-616 273 16 and and CCONJ cana-616 273 17 f1measure f1measure NOUN cana-616 273 18 . . PUNCT cana-616 274 1 the the DET cana-616 274 2 best good ADJ cana-616 274 3 alg alg NOUN cana-616 274 4 was be AUX cana-616 274 5 random random ADJ cana-616 274 6 forest forest NOUN cana-616 274 7 classifier classifier NOUN cana-616 274 8 in in ADP cana-616 274 9 this this DET cana-616 274 10 instance instance NOUN cana-616 274 11 that that PRON cana-616 274 12 displayed display VERB cana-616 274 13 the the DET cana-616 274 14 high high ADJ cana-616 274 15 scores score NOUN cana-616 274 16 on on ADP cana-616 274 17 most most ADJ cana-616 274 18 of of ADP cana-616 274 19 the the DET cana-616 274 20 metrics metric NOUN cana-616 274 21 , , PUNCT cana-616 274 22 particularly particularly ADV cana-616 274 23 , , PUNCT cana-616 274 24 the the DET cana-616 274 25 highest high ADJ cana-616 274 26 on on ADP cana-616 274 27 accuracy accuracy NOUN cana-616 274 28 ( ( PUNCT cana-616 274 29 96 96 NUM cana-616 274 30 ) ) PUNCT cana-616 274 31 . . PUNCT cana-616 275 1 0 0 X cana-616 275 2 . . X cana-616 276 1 92 92 NUM cana-616 276 2 ( ( PUNCT cana-616 276 3 accuracy accuracy NOUN cana-616 276 4 rate rate NOUN cana-616 276 5 ) ) PUNCT cana-616 276 6 and and CCONJ cana-616 276 7 0 0 NUM cana-616 276 8 . . NOUN cana-616 276 9 83(f1score 83(f1score NUM cana-616 276 10 ) ) PUNCT cana-616 276 11 show show VERB cana-616 276 12 the the DET cana-616 276 13 result result NOUN cana-616 276 14 of of ADP cana-616 276 15 class1 class1 NOUN cana-616 276 16 . . PUNCT cana-616 277 1 it it PRON cana-616 277 2 might might AUX cana-616 277 3 be be AUX cana-616 277 4 even even ADV cana-616 277 5 more more ADV cana-616 277 6 helpful helpful ADJ cana-616 277 7 because because SCONJ cana-616 277 8 it it PRON cana-616 277 9 tackles tackle VERB cana-616 277 10 the the DET cana-616 277 11 problem problem NOUN cana-616 277 12 of of ADP cana-616 277 13 linearity linearity NOUN cana-616 277 14 and and CCONJ cana-616 277 15 non non ADJ cana-616 277 16 - - ADJ cana-616 277 17 linear linear ADJ cana-616 277 18 data datum NOUN cana-616 277 19 . . PUNCT cana-616 278 1 random random ADJ cana-616 278 2 forest forest NOUN cana-616 278 3 classifier classifier NOUN cana-616 278 4 : : PUNCT cana-616 278 5 the the DET cana-616 278 6 centralizing centralizing NOUN cana-616 278 7 by by ADP cana-616 278 8 the the DET cana-616 278 9 excellent excellent ADJ cana-616 278 10 performance performance NOUN cana-616 278 11 in in ADP cana-616 278 12 terms term NOUN cana-616 278 13 of of ADP cana-616 278 14 the the DET cana-616 278 15 precision precision NOUN cana-616 278 16 rate rate NOUN cana-616 278 17 ( ( PUNCT cana-616 278 18 99 99 NUM cana-616 278 19 % % NOUN cana-616 278 20 for for ADP cana-616 278 21 class class NOUN cana-616 278 22 0 0 NUM cana-616 278 23 and and CCONJ cana-616 278 24 78 78 NUM cana-616 278 25 % % NOUN cana-616 278 26 for for ADP cana-616 278 27 class class NOUN cana-616 278 28 1 1 NUM cana-616 278 29 ) ) PUNCT cana-616 278 30 and and CCONJ cana-616 278 31 the the DET cana-616 278 32 recall recall NOUN cana-616 278 33 rates rate NOUN cana-616 278 34 ( ( PUNCT cana-616 278 35 97 97 NUM cana-616 278 36 % % NOUN cana-616 278 37 for for ADP cana-616 278 38 class class NOUN cana-616 278 39 0 0 NUM cana-616 278 40 and and CCONJ cana-616 278 41 89 89 NUM cana-616 278 42 % % NOUN cana-616 278 43 for for ADP cana-616 278 44 class class NOUN cana-616 278 45 1 1 NUM cana-616 278 46 ) ) PUNCT cana-616 278 47 . . PUNCT cana-616 279 1 a a DET cana-616 279 2 normal normal ADJ cana-616 279 3 distribution distribution NOUN cana-616 279 4 around around ADV cana-616 279 5 between between ADP cana-616 279 6 the the DET cana-616 279 7 classes class NOUN cana-616 279 8 manifests manifest VERB cana-616 279 9 that that SCONJ cana-616 279 10 the the DET cana-616 279 11 model model NOUN cana-616 279 12 is be AUX cana-616 279 13 not not PART cana-616 279 14 overfitted overfitte VERB cana-616 279 15 . . PUNCT cana-616 280 1 decision decision NOUN cana-616 280 2 tree tree NOUN cana-616 280 3 classifier classifier NOUN cana-616 280 4 : : PUNCT cana-616 280 5 this this DET cana-616 280 6 model model NOUN cana-616 280 7 also also ADV cana-616 280 8 showed show VERB cana-616 280 9 high high ADJ cana-616 280 10 accuracy accuracy NOUN cana-616 280 11 and and CCONJ cana-616 280 12 a a DET cana-616 280 13 good good ADJ cana-616 280 14 balance balance NOUN cana-616 280 15 between between ADP cana-616 280 16 precision precision NOUN cana-616 280 17 and and CCONJ cana-616 280 18 recall recall NOUN cana-616 280 19 , , PUNCT cana-616 280 20 although although SCONJ cana-616 280 21 slightly slightly ADV cana-616 280 22 lower low ADJ cana-616 280 23 than than ADP cana-616 280 24 the the DET cana-616 280 25 random random ADJ cana-616 280 26 forest forest NOUN cana-616 280 27 . . PUNCT cana-616 281 1 communications communication NOUN cana-616 281 2 on on ADP cana-616 281 3 applied apply VERB cana-616 281 4 nonlinear nonlinear ADJ cana-616 281 5 analysis analysis NOUN cana-616 281 6 issn issn NOUN cana-616 281 7 : : PUNCT cana-616 281 8 1074 1074 NUM cana-616 281 9 - - PUNCT cana-616 281 10 133x 133x NUM cana-616 281 11 vol vol NOUN cana-616 281 12 31 31 NUM cana-616 281 13 no no NOUN cana-616 281 14 . . PUNCT cana-616 282 1 2s 2s NUM cana-616 282 2 ( ( PUNCT cana-616 282 3 2024 2024 NUM cana-616 282 4 ) ) PUNCT cana-616 282 5 141 141 NUM cana-616 282 6 https://internationalpubls.com https://internationalpubls.com SYM cana-616 282 7 β€’ β€’ NOUN cana-616 282 8 k k PROPN cana-616 282 9 neighbors neighbor NOUN cana-616 282 10 classifier classifier VERB cana-616 282 11 : : PUNCT cana-616 282 12 in in ADP cana-616 282 13 cases case NOUN cana-616 282 14 related relate VERB cana-616 282 15 to to ADP cana-616 282 16 the the DET cana-616 282 17 class class NOUN cana-616 282 18 1 1 NUM cana-616 282 19 majority majority NOUN cana-616 282 20 , , PUNCT cana-616 282 21 it it PRON cana-616 282 22 scored score VERB cana-616 282 23 the the DET cana-616 282 24 best good ADJ cana-616 282 25 in in ADP cana-616 282 26 terms term NOUN cana-616 282 27 of of ADP cana-616 282 28 recall recall NOUN cana-616 282 29 ( ( PUNCT cana-616 282 30 93 93 NUM cana-616 282 31 % % NOUN cana-616 282 32 ) ) PUNCT cana-616 282 33 , , PUNCT cana-616 282 34 which which PRON cana-616 282 35 testifies testify VERB cana-616 282 36 to to ADP cana-616 282 37 its its PRON cana-616 282 38 sensitivity sensitivity NOUN cana-616 282 39 towards towards ADP cana-616 282 40 class class NOUN cana-616 282 41 1 1 NUM cana-616 282 42 but but CCONJ cana-616 282 43 showed show VERB cana-616 282 44 poorer poor ADJ cana-616 282 45 precision precision NOUN cana-616 282 46 ( ( PUNCT cana-616 282 47 59 59 NUM cana-616 282 48 % % NOUN cana-616 282 49 ) ) PUNCT cana-616 282 50 for for ADP cana-616 282 51 class class NOUN cana-616 282 52 1 1 NUM cana-616 282 53 and and CCONJ cana-616 282 54 higher high ADJ cana-616 282 55 number number NOUN cana-616 282 56 of of ADP cana-616 282 57 false false ADJ cana-616 282 58 positives positive NOUN cana-616 282 59 . . PUNCT cana-616 283 1 β€’ β€’ NUM cana-616 283 2 gaussian gaussian PROPN cana-616 283 3 nb nb INTJ cana-616 283 4 : : PUNCT cana-616 283 5 while while SCONJ cana-616 283 6 it it PRON cana-616 283 7 had have VERB cana-616 283 8 commendable commendable ADJ cana-616 283 9 recall recall NOUN cana-616 283 10 for for ADP cana-616 283 11 class class NOUN cana-616 283 12 1 1 NUM cana-616 283 13 ( ( PUNCT cana-616 283 14 88 88 NUM cana-616 283 15 % % NOUN cana-616 283 16 ) ) PUNCT cana-616 283 17 , , PUNCT cana-616 283 18 its its PRON cana-616 283 19 precision precision NOUN cana-616 283 20 for for ADP cana-616 283 21 class class NOUN cana-616 283 22 1 1 NUM cana-616 283 23 was be AUX cana-616 283 24 relatively relatively ADV cana-616 283 25 low low ADJ cana-616 283 26 ( ( PUNCT cana-616 283 27 47 47 NUM cana-616 283 28 % % NOUN cana-616 283 29 ) ) PUNCT cana-616 283 30 , , PUNCT cana-616 283 31 which which PRON cana-616 283 32 could could AUX cana-616 283 33 be be AUX cana-616 283 34 problematic problematic ADJ cana-616 283 35 in in ADP cana-616 283 36 scenarios scenario NOUN cana-616 283 37 where where SCONJ cana-616 283 38 false false ADJ cana-616 283 39 positives positive NOUN cana-616 283 40 are be AUX cana-616 283 41 a a DET cana-616 283 42 critical critical ADJ cana-616 283 43 concern concern NOUN cana-616 283 44 . . PUNCT cana-616 284 1 β€’ β€’ NUM cana-616 284 2 logistic logistic ADJ cana-616 284 3 regression regression NOUN cana-616 284 4 : : PUNCT cana-616 284 5 showed show VERB cana-616 284 6 the the DET cana-616 284 7 least least ADJ cana-616 284 8 effective effective ADJ cana-616 284 9 performance performance NOUN cana-616 284 10 , , PUNCT cana-616 284 11 particularly particularly ADV cana-616 284 12 struggling struggle VERB cana-616 284 13 with with ADP cana-616 284 14 class class NOUN cana-616 284 15 1 1 NUM cana-616 284 16 predictions prediction NOUN cana-616 284 17 , , PUNCT cana-616 284 18 which which PRON cana-616 284 19 could could AUX cana-616 284 20 be be AUX cana-616 284 21 attributed attribute VERB cana-616 284 22 to to ADP cana-616 284 23 its its PRON cana-616 284 24 linear linear ADJ cana-616 284 25 nature nature NOUN cana-616 284 26 and and CCONJ cana-616 284 27 the the DET cana-616 284 28 possible possible ADJ cana-616 284 29 non non ADJ cana-616 284 30 - - ADJ cana-616 284 31 linear linear ADJ cana-616 284 32 relationships relationship NOUN cana-616 284 33 in in ADP cana-616 284 34 the the DET cana-616 284 35 data datum NOUN cana-616 284 36 . . PUNCT cana-616 285 1 key key ADJ cana-616 285 2 findings finding NOUN cana-616 285 3 epidemiological epidemiological ADJ cana-616 285 4 patterns pattern NOUN cana-616 285 5 : : PUNCT cana-616 285 6 the the DET cana-616 285 7 exploratory exploratory ADJ cana-616 285 8 data datum NOUN cana-616 285 9 on on ADP cana-616 285 10 the the DET cana-616 285 11 popularity popularity NOUN cana-616 285 12 of of ADP cana-616 285 13 lsd lsd NOUN cana-616 285 14 had have AUX cana-616 285 15 a a DET cana-616 285 16 distinctly distinctly ADV cana-616 285 17 regional regional ADJ cana-616 285 18 and and CCONJ cana-616 285 19 temporal temporal ADJ cana-616 285 20 pattern pattern NOUN cana-616 285 21 demonstrating demonstrate VERB cana-616 285 22 its its PRON cana-616 285 23 usage usage NOUN cana-616 285 24 in in ADP cana-616 285 25 some some DET cana-616 285 26 areas area NOUN cana-616 285 27 and and CCONJ cana-616 285 28 nonuse nonuse VERB cana-616 285 29 in in ADP cana-616 285 30 others other NOUN cana-616 285 31 . . PUNCT cana-616 286 1 analyzing analyze VERB cana-616 286 2 statistics statistic NOUN cana-616 286 3 about about ADP cana-616 286 4 that that DET cana-616 286 5 lsd lsd NOUN cana-616 286 6 is be AUX cana-616 286 7 connected connect VERB cana-616 286 8 with with ADP cana-616 286 9 the the DET cana-616 286 10 environment environment NOUN cana-616 286 11 , , PUNCT cana-616 286 12 animal animal NOUN cana-616 286 13 statistical statistical ADJ cana-616 286 14 background background NOUN cana-616 286 15 , , PUNCT cana-616 286 16 and and CCONJ cana-616 286 17 the the DET cana-616 286 18 incidence incidence NOUN cana-616 286 19 through through ADP cana-616 286 20 it it PRON cana-616 286 21 results result VERB cana-616 286 22 in in ADP cana-616 286 23 a a DET cana-616 286 24 precise precise ADJ cana-616 286 25 picture picture NOUN cana-616 286 26 . . PUNCT cana-616 287 1 another another DET cana-616 287 2 very very ADV cana-616 287 3 relevant relevant ADJ cana-616 287 4 issue issue NOUN cana-616 287 5 is be AUX cana-616 287 6 the the DET cana-616 287 7 occurrence occurrence NOUN cana-616 287 8 of of ADP cana-616 287 9 areas area NOUN cana-616 287 10 determined determine VERB cana-616 287 11 by by ADP cana-616 287 12 certain certain ADJ cana-616 287 13 types type NOUN cana-616 287 14 of of ADP cana-616 287 15 climatic climatic ADJ cana-616 287 16 conditions condition NOUN cana-616 287 17 and and CCONJ cana-616 287 18 common common ADJ cana-616 287 19 practices practice NOUN cana-616 287 20 of of ADP cana-616 287 21 animal animal NOUN cana-616 287 22 breeding breeding NOUN cana-616 287 23 have have AUX cana-616 287 24 had have VERB cana-616 287 25 higher high ADJ cana-616 287 26 spread spread NOUN cana-616 287 27 , , PUNCT cana-616 287 28 thus thus ADV cana-616 287 29 not not PART cana-616 287 30 isolating isolate VERB cana-616 287 31 limited limited ADJ cana-616 287 32 actions action NOUN cana-616 287 33 might might AUX cana-616 287 34 not not PART cana-616 287 35 be be AUX cana-616 287 36 enough enough ADJ cana-616 287 37 . . PUNCT cana-616 288 1 statistical statistical ADJ cana-616 288 2 insights insight NOUN cana-616 288 3 : : PUNCT cana-616 288 4 there there PRON cana-616 288 5 were be VERB cana-616 288 6 sectors sector NOUN cana-616 288 7 in in ADP cana-616 288 8 the the DET cana-616 288 9 study study NOUN cana-616 288 10 that that PRON cana-616 288 11 were be AUX cana-616 288 12 statistically statistically ADV cana-616 288 13 proved prove VERB cana-616 288 14 to to PART cana-616 288 15 be be AUX cana-616 288 16 risk risk NOUN cana-616 288 17 factors factor NOUN cana-616 288 18 of of ADP cana-616 288 19 lsd lsd NOUN cana-616 288 20 and and CCONJ cana-616 288 21 other other ADJ cana-616 288 22 serious serious ADJ cana-616 288 23 manifestations manifestation NOUN cana-616 288 24 of of ADP cana-616 288 25 the the DET cana-616 288 26 disease disease NOUN cana-616 288 27 . . PUNCT cana-616 289 1 besides besides SCONJ cana-616 289 2 , , PUNCT cana-616 289 3 these these DET cana-616 289 4 concerns concern NOUN cana-616 289 5 gave give VERB cana-616 289 6 other other ADJ cana-616 289 7 scholars scholar NOUN cana-616 289 8 a a DET cana-616 289 9 reason reason NOUN cana-616 289 10 to to PART cana-616 289 11 conduct conduct VERB cana-616 289 12 other other ADJ cana-616 289 13 practical practical ADJ cana-616 289 14 studies study NOUN cana-616 289 15 which which PRON cana-616 289 16 then then ADV cana-616 289 17 led lead VERB cana-616 289 18 and and CCONJ cana-616 289 19 tested test VERB cana-616 289 20 the the DET cana-616 289 21 spread spread NOUN cana-616 289 22 and and CCONJ cana-616 289 23 the the DET cana-616 289 24 severity severity NOUN cana-616 289 25 of of ADP cana-616 289 26 the the DET cana-616 289 27 disease disease NOUN cana-616 289 28 . . PUNCT cana-616 290 1 however however ADV cana-616 290 2 , , PUNCT cana-616 290 3 such such ADJ cana-616 290 4 analysis analysis NOUN cana-616 290 5 would would AUX cana-616 290 6 also also ADV cana-616 290 7 illustrate illustrate VERB cana-616 290 8 that that SCONJ cana-616 290 9 different different ADJ cana-616 290 10 dog dog NOUN cana-616 290 11 breeds breed NOUN cana-616 290 12 have have VERB cana-616 290 13 the the DET cana-616 290 14 varied varied ADJ cana-616 290 15 risk risk NOUN cana-616 290 16 for for SCONJ cana-616 290 17 them they PRON cana-616 290 18 to to PART cana-616 290 19 get get VERB cana-616 290 20 the the DET cana-616 290 21 disease disease NOUN cana-616 290 22 . . PUNCT cana-616 291 1 in in ADP cana-616 291 2 other other ADJ cana-616 291 3 words word NOUN cana-616 291 4 , , PUNCT cana-616 291 5 it it PRON cana-616 291 6 could could AUX cana-616 291 7 be be AUX cana-616 291 8 genetic genetic ADJ cana-616 291 9 or or CCONJ cana-616 291 10 environmental environmental ADJ cana-616 291 11 factor factor NOUN cana-616 291 12 that that PRON cana-616 291 13 influence influence VERB cana-616 291 14 the the DET cana-616 291 15 virulence virulence NOUN cana-616 291 16 of of ADP cana-616 291 17 lsd lsd NOUN cana-616 291 18 . . PUNCT cana-616 292 1 predictive predictive ADJ cana-616 292 2 modeling modeling NOUN cana-616 292 3 : : PUNCT cana-616 292 4 in in ADP cana-616 292 5 this this DET cana-616 292 6 training training NOUN cana-616 292 7 machine machine NOUN cana-616 292 8 learning learning NOUN cana-616 292 9 models model NOUN cana-616 292 10 , , PUNCT cana-616 292 11 not not PART cana-616 292 12 just just ADV cana-616 292 13 the the DET cana-616 292 14 lsd lsd NOUN cana-616 292 15 detection detection NOUN cana-616 292 16 but but CCONJ cana-616 292 17 even even ADV cana-616 292 18 suggestion suggestion NOUN cana-616 292 19 and and CCONJ cana-616 292 20 recommendation recommendation NOUN cana-616 292 21 of of ADP cana-616 292 22 healthy healthy ADJ cana-616 292 23 fruits fruit NOUN cana-616 292 24 and and CCONJ cana-616 292 25 vegetables vegetable NOUN cana-616 292 26 in in ADP cana-616 292 27 the the DET cana-616 292 28 study study NOUN cana-616 292 29 participants participant NOUN cana-616 292 30 ' ' PART cana-616 292 31 diets diet NOUN cana-616 292 32 are be AUX cana-616 292 33 included include VERB cana-616 292 34 . . PUNCT cana-616 293 1 due due ADP cana-616 293 2 to to ADP cana-616 293 3 the the DET cana-616 293 4 types type NOUN cana-616 293 5 of of ADP cana-616 293 6 algorithms algorithm NOUN cana-616 293 7 such such ADJ cana-616 293 8 as as ADP cana-616 293 9 random random ADJ cana-616 293 10 forest forest NOUN cana-616 293 11 and and CCONJ cana-616 293 12 gradient gradient NOUN cana-616 293 13 boosting boosting NOUN cana-616 293 14 , , PUNCT cana-616 293 15 where where SCONJ cana-616 293 16 the the DET cana-616 293 17 accuracy accuracy NOUN cana-616 293 18 is be AUX cana-616 293 19 still still ADV cana-616 293 20 high high ADJ cana-616 293 21 even even ADV cana-616 293 22 with with ADP cana-616 293 23 the the DET cana-616 293 24 datasets dataset NOUN cana-616 293 25 which which PRON cana-616 293 26 are be AUX cana-616 293 27 complex complex ADJ cana-616 293 28 across across ADP cana-616 293 29 multiple multiple ADJ cana-616 293 30 input input NOUN cana-616 293 31 variables variable NOUN cana-616 293 32 , , PUNCT cana-616 293 33 it it PRON cana-616 293 34 is be AUX cana-616 293 35 not not PART cana-616 293 36 absolute absolute ADJ cana-616 293 37 to to PART cana-616 293 38 think think VERB cana-616 293 39 that that SCONJ cana-616 293 40 recurrence recurrence NOUN cana-616 293 41 of of ADP cana-616 293 42 diseases disease NOUN cana-616 293 43 only only ADV cana-616 293 44 grows grow VERB cana-616 293 45 from from ADP cana-616 293 46 the the DET cana-616 293 47 existence existence NOUN cana-616 293 48 of of ADP cana-616 293 49 a a DET cana-616 293 50 few few ADJ cana-616 293 51 risk risk NOUN cana-616 293 52 factors factor NOUN cana-616 293 53 . . PUNCT cana-616 294 1 the the DET cana-616 294 2 diagnostic diagnostic ADJ cana-616 294 3 ranks rank NOUN cana-616 294 4 shown show VERB cana-616 294 5 that that SCONJ cana-616 294 6 the the DET cana-616 294 7 specific specific ADJ cana-616 294 8 characteristics characteristic NOUN cana-616 294 9 were be AUX cana-616 294 10 critical critical ADJ cana-616 294 11 in in ADP cana-616 294 12 distinguishing distinguish VERB cana-616 294 13 the the DET cana-616 294 14 main main ADJ cana-616 294 15 grammes gramme NOUN cana-616 294 16 of of ADP cana-616 294 17 infection infection NOUN cana-616 294 18 , , PUNCT cana-616 294 19 which which PRON cana-616 294 20 included include VERB cana-616 294 21 their their PRON cana-616 294 22 distance distance NOUN cana-616 294 23 from from ADP cana-616 294 24 the the DET cana-616 294 25 infectious infectious ADJ cana-616 294 26 patients patient NOUN cana-616 294 27 , , PUNCT cana-616 294 28 their their PRON cana-616 294 29 vaccination vaccination NOUN cana-616 294 30 status status NOUN cana-616 294 31 and and CCONJ cana-616 294 32 a a DET cana-616 294 33 particular particular ADJ cana-616 294 34 combination combination NOUN cana-616 294 35 of of ADP cana-616 294 36 the the DET cana-616 294 37 symptoms symptom NOUN cana-616 294 38 . . PUNCT cana-616 295 1 key key ADJ cana-616 295 2 insights insight NOUN cana-616 295 3 and and CCONJ cana-616 295 4 recommendations recommendation NOUN cana-616 295 5 model model NOUN cana-616 295 6 selection selection NOUN cana-616 295 7 : : PUNCT cana-616 295 8 the the DET cana-616 295 9 cost cost NOUN cana-616 295 10 of of ADP cana-616 295 11 a a DET cana-616 295 12 false false ADJ cana-616 295 13 negative negative NOUN cana-616 295 14 and and CCONJ cana-616 295 15 a a DET cana-616 295 16 false false ADJ cana-616 295 17 positive positive ADJ cana-616 295 18 matters matter NOUN cana-616 295 19 and and CCONJ cana-616 295 20 different different ADJ cana-616 295 21 workers worker NOUN cana-616 295 22 ’ ' PUNCT cana-616 295 23 models model NOUN cana-616 295 24 might might AUX cana-616 295 25 predominate predominate VERB cana-616 295 26 . . PUNCT cana-616 296 1 if if SCONJ cana-616 296 2 the the DET cana-616 296 3 tendency tendency NOUN cana-616 296 4 is be AUX cana-616 296 5 minimizing minimize VERB cana-616 296 6 false false ADJ cana-616 296 7 negatives negative NOUN cana-616 296 8 , , PUNCT cana-616 296 9 kneighbors kneighbor NOUN cana-616 296 10 or or CCONJ cana-616 296 11 gaussiannb gaussiannb ADJ cana-616 296 12 algorithms algorithm NOUN cana-616 296 13 , , PUNCT cana-616 296 14 low low ADJ cana-616 296 15 in in ADP cana-616 296 16 precision precision NOUN cana-616 296 17 but but CCONJ cana-616 296 18 effective effective ADJ cana-616 296 19 , , PUNCT cana-616 296 20 can can AUX cana-616 296 21 be be AUX cana-616 296 22 the the DET cana-616 296 23 solution solution NOUN cana-616 296 24 . . PUNCT cana-616 297 1 balanced balanced ADJ cana-616 297 2 approach approach NOUN cana-616 297 3 is be AUX cana-616 297 4 better well ADV cana-616 297 5 represented represent VERB cana-616 297 6 with with ADP cana-616 297 7 the the DET cana-616 297 8 help help NOUN cana-616 297 9 of of ADP cana-616 297 10 random random ADJ cana-616 297 11 forest forest NOUN cana-616 297 12 or or CCONJ cana-616 297 13 decision decision NOUN cana-616 297 14 tree tree NOUN cana-616 297 15 models model NOUN cana-616 297 16 . . PUNCT cana-616 298 1 feature feature NOUN cana-616 298 2 importance importance NOUN cana-616 298 3 : : PUNCT cana-616 298 4 through through ADP cana-616 298 5 feature feature NOUN cana-616 298 6 selection selection NOUN cana-616 298 7 , , PUNCT cana-616 298 8 the the DET cana-616 298 9 difference difference NOUN cana-616 298 10 can can AUX cana-616 298 11 be be AUX cana-616 298 12 observed observe VERB cana-616 298 13 in in ADP cana-616 298 14 the the DET cana-616 298 15 dependence dependence NOUN cana-616 298 16 of of ADP cana-616 298 17 the the DET cana-616 298 18 features feature NOUN cana-616 298 19 on on ADP cana-616 298 20 the the DET cana-616 298 21 predictions prediction NOUN cana-616 298 22 of of ADP cana-616 298 23 the the DET cana-616 298 24 model model NOUN cana-616 298 25 can can AUX cana-616 298 26 be be AUX cana-616 298 27 followed follow VERB cana-616 298 28 here here ADV cana-616 298 29 as as SCONJ cana-616 298 30 provided provide VERB cana-616 298 31 by by ADP cana-616 298 32 the the DET cana-616 298 33 tree tree NOUN cana-616 298 34 - - PUNCT cana-616 298 35 based base VERB cana-616 298 36 models model NOUN cana-616 298 37 . . PUNCT cana-616 299 1 this this PRON cana-616 299 2 gives give VERB cana-616 299 3 us we PRON cana-616 299 4 the the DET cana-616 299 5 opportunity opportunity NOUN cana-616 299 6 to to PART cana-616 299 7 continue continue VERB cana-616 299 8 improving improve VERB cana-616 299 9 the the DET cana-616 299 10 models model NOUN cana-616 299 11 , , PUNCT cana-616 299 12 by by ADP cana-616 299 13 turning turn VERB cana-616 299 14 to to ADP cana-616 299 15 the the DET cana-616 299 16 really really ADV cana-616 299 17 significant significant ADJ cana-616 299 18 variables variable NOUN cana-616 299 19 . . PUNCT cana-616 300 1 communications communication NOUN cana-616 300 2 on on ADP cana-616 300 3 applied apply VERB cana-616 300 4 nonlinear nonlinear ADJ cana-616 300 5 analysis analysis NOUN cana-616 300 6 issn issn NOUN cana-616 300 7 : : PUNCT cana-616 300 8 1074 1074 NUM cana-616 300 9 - - PUNCT cana-616 300 10 133x 133x NUM cana-616 300 11 vol vol NOUN cana-616 300 12 31 31 NUM cana-616 300 13 no no NOUN cana-616 300 14 . . PUNCT cana-616 301 1 2s 2s NUM cana-616 301 2 ( ( PUNCT cana-616 301 3 2024 2024 NUM cana-616 301 4 ) ) PUNCT cana-616 301 5 142 142 NUM cana-616 301 6 https://internationalpubls.com https://internationalpubls.com NUM cana-616 301 7 continued continue VERB cana-616 301 8 monitoring monitoring NOUN cana-616 301 9 and and CCONJ cana-616 301 10 updating updating NOUN cana-616 301 11 : : PUNCT cana-616 301 12 it it PRON cana-616 301 13 is be AUX cana-616 301 14 , , PUNCT cana-616 301 15 therefore therefore ADV cana-616 301 16 , , PUNCT cana-616 301 17 the the DET cana-616 301 18 responsibility responsibility NOUN cana-616 301 19 of of ADP cana-616 301 20 the the DET cana-616 301 21 designers designer NOUN cana-616 301 22 to to PART cana-616 301 23 keep keep VERB cana-616 301 24 tabs tab NOUN cana-616 301 25 on on ADP cana-616 301 26 the the DET cana-616 301 27 models model NOUN cana-616 301 28 and and CCONJ cana-616 301 29 review review VERB cana-616 301 30 periodically periodically ADV cana-616 301 31 with with ADP cana-616 301 32 any any DET cana-616 301 33 new new ADJ cana-616 301 34 data datum NOUN cana-616 301 35 that that PRON cana-616 301 36 is be AUX cana-616 301 37 acquired acquire VERB cana-616 301 38 to to PART cana-616 301 39 ensure ensure VERB cana-616 301 40 they they PRON cana-616 301 41 are be AUX cana-616 301 42 reflective reflective ADJ cana-616 301 43 of of ADP cana-616 301 44 the the DET cana-616 301 45 dynamic dynamic ADJ cana-616 301 46 patterns pattern NOUN cana-616 301 47 over over ADP cana-616 301 48 time time NOUN cana-616 301 49 which which PRON cana-616 301 50 might might AUX cana-616 301 51 change change VERB cana-616 301 52 . . PUNCT cana-616 302 1 expanding expand VERB cana-616 302 2 data datum NOUN cana-616 302 3 collection collection NOUN cana-616 302 4 : : PUNCT cana-616 302 5 we we PRON cana-616 302 6 can can AUX cana-616 302 7 help help VERB cana-616 302 8 improve improve VERB cana-616 302 9 model model NOUN cana-616 302 10 reliability reliability NOUN cana-616 302 11 by by ADP cana-616 302 12 using use VERB cana-616 302 13 more more ADV cana-616 302 14 diverse diverse ADJ cana-616 302 15 and and CCONJ cana-616 302 16 voluminous voluminous ADJ cana-616 302 17 data datum NOUN cana-616 302 18 , , PUNCT cana-616 302 19 especially especially ADV cana-616 302 20 for for ADP cana-616 302 21 low low ADJ cana-616 302 22 represented represent VERB cana-616 302 23 classes class NOUN cana-616 302 24 , , PUNCT cana-616 302 25 which which PRON cana-616 302 26 in in ADP cana-616 302 27 turns turn NOUN cana-616 302 28 will will AUX cana-616 302 29 strengthen strengthen VERB cana-616 302 30 the the DET cana-616 302 31 results result NOUN cana-616 302 32 besides besides SCONJ cana-616 302 33 varying vary VERB cana-616 302 34 different different ADJ cana-616 302 35 situations situation NOUN cana-616 302 36 advanced advanced ADJ cana-616 302 37 techniques technique NOUN cana-616 302 38 : : PUNCT cana-616 302 39 apart apart ADV cana-616 302 40 from from ADP cana-616 302 41 examining examine VERB cana-616 302 42 advanced advanced ADJ cana-616 302 43 techniques technique NOUN cana-616 302 44 such such ADJ cana-616 302 45 as as ADP cana-616 302 46 ensemble ensemble ADJ cana-616 302 47 learning learning NOUN cana-616 302 48 and and CCONJ cana-616 302 49 boosting boost VERB cana-616 302 50 , , PUNCT cana-616 302 51 going go VERB cana-616 302 52 a a DET cana-616 302 53 step step NOUN cana-616 302 54 further far ADV cana-616 302 55 with with ADP cana-616 302 56 deep deep ADJ cana-616 302 57 learning learning NOUN cana-616 302 58 models model NOUN cana-616 302 59 will will AUX cana-616 302 60 always always ADV cana-616 302 61 give give VERB cana-616 302 62 a a DET cana-616 302 63 better well ADJ cana-616 302 64 outcome outcome NOUN cana-616 302 65 , , PUNCT cana-616 302 66 especially especially ADV cana-616 302 67 when when SCONJ cana-616 302 68 dealing deal VERB cana-616 302 69 with with ADP cana-616 302 70 large large ADJ cana-616 302 71 and and CCONJ cana-616 302 72 complex complex ADJ cana-616 302 73 datasets dataset NOUN cana-616 302 74 such such ADJ cana-616 302 75 as as ADP cana-616 302 76 this this PRON cana-616 302 77 . . PUNCT cana-616 303 1 the the DET cana-616 303 2 integration integration NOUN cana-616 303 3 of of ADP cana-616 303 4 these these DET cana-616 303 5 advanced advanced ADJ cana-616 303 6 mathematical mathematical ADJ cana-616 303 7 techniques technique NOUN cana-616 303 8 into into ADP cana-616 303 9 random random ADJ cana-616 303 10 forest forest NOUN cana-616 303 11 classifiers classifier NOUN cana-616 303 12 represents represent VERB cana-616 303 13 a a DET cana-616 303 14 significant significant ADJ cana-616 303 15 leap leap NOUN cana-616 303 16 forward forward ADV cana-616 303 17 in in ADP cana-616 303 18 the the DET cana-616 303 19 development development NOUN cana-616 303 20 of of ADP cana-616 303 21 machine machine NOUN cana-616 303 22 learning learning NOUN cana-616 303 23 models model NOUN cana-616 303 24 capable capable ADJ cana-616 303 25 of of ADP cana-616 303 26 handling handle VERB cana-616 303 27 complex complex ADJ cana-616 303 28 , , PUNCT cana-616 303 29 nuanced nuanced ADJ cana-616 303 30 tasks task NOUN cana-616 303 31 such such ADJ cana-616 303 32 as as ADP cana-616 303 33 image image NOUN cana-616 303 34 - - PUNCT cana-616 303 35 based base VERB cana-616 303 36 classification classification NOUN cana-616 303 37 for for ADP cana-616 303 38 disease disease NOUN cana-616 303 39 detection detection NOUN cana-616 303 40 . . PUNCT cana-616 304 1 this this DET cana-616 304 2 integration integration NOUN cana-616 304 3 not not PART cana-616 304 4 only only ADV cana-616 304 5 enhances enhance VERB cana-616 304 6 the the DET cana-616 304 7 predictive predictive ADJ cana-616 304 8 accuracy accuracy NOUN cana-616 304 9 but but CCONJ cana-616 304 10 also also ADV cana-616 304 11 improves improve VERB cana-616 304 12 the the DET cana-616 304 13 model model NOUN cana-616 304 14 's 's PART cana-616 304 15 interpretability interpretability NOUN cana-616 304 16 and and CCONJ cana-616 304 17 adaptability adaptability NOUN cana-616 304 18 to to ADP cana-616 304 19 new new ADJ cana-616 304 20 challenges challenge NOUN cana-616 304 21 . . PUNCT cana-616 305 1 through through ADP cana-616 305 2 the the DET cana-616 305 3 strategic strategic ADJ cana-616 305 4 application application NOUN cana-616 305 5 of of ADP cana-616 305 6 bayesian bayesian NOUN cana-616 305 7 optimization optimization NOUN cana-616 305 8 , , PUNCT cana-616 305 9 gradient gradient NOUN cana-616 305 10 and and CCONJ cana-616 305 11 hessian hessian ADJ cana-616 305 12 computations computation NOUN cana-616 305 13 , , PUNCT cana-616 305 14 advanced advanced ADJ cana-616 305 15 evaluation evaluation NOUN cana-616 305 16 metrics metric NOUN cana-616 305 17 , , PUNCT cana-616 305 18 and and CCONJ cana-616 305 19 regularization regularization NOUN cana-616 305 20 techniques technique NOUN cana-616 305 21 , , PUNCT cana-616 305 22 rf rf NOUN cana-616 305 23 classifiers classifier NOUN cana-616 305 24 can can AUX cana-616 305 25 be be AUX cana-616 305 26 tailored tailor VERB cana-616 305 27 to to PART cana-616 305 28 meet meet VERB cana-616 305 29 specific specific ADJ cana-616 305 30 performance performance NOUN cana-616 305 31 criteria criterion NOUN cana-616 305 32 , , PUNCT cana-616 305 33 ensuring ensure VERB cana-616 305 34 their their PRON cana-616 305 35 effectiveness effectiveness NOUN cana-616 305 36 in in ADP cana-616 305 37 critical critical ADJ cana-616 305 38 applications application NOUN cana-616 305 39 across across ADP cana-616 305 40 various various ADJ cana-616 305 41 fields field NOUN cana-616 305 42 . . PUNCT cana-616 306 1 this this DET cana-616 306 2 holistic holistic ADJ cana-616 306 3 approach approach NOUN cana-616 306 4 to to ADP cana-616 306 5 model model NOUN cana-616 306 6 refinement refinement NOUN cana-616 306 7 underscores underscore VERB cana-616 306 8 the the DET cana-616 306 9 importance importance NOUN cana-616 306 10 of of ADP cana-616 306 11 a a DET cana-616 306 12 deep deep ADJ cana-616 306 13 mathematical mathematical ADJ cana-616 306 14 foundation foundation NOUN cana-616 306 15 in in ADP cana-616 306 16 driving drive VERB cana-616 306 17 the the DET cana-616 306 18 evolution evolution NOUN cana-616 306 19 of of ADP cana-616 306 20 machine machine NOUN cana-616 306 21 learning learning NOUN cana-616 306 22 technologies technology NOUN cana-616 306 23 . . PUNCT cana-616 307 1 implications implication NOUN cana-616 307 2 for for ADP cana-616 307 3 veterinary veterinary ADJ cana-616 307 4 health health NOUN cana-616 307 5 and and CCONJ cana-616 307 6 policy policy NOUN cana-616 307 7 policy policy NOUN cana-616 307 8 development development NOUN cana-616 307 9 : : PUNCT cana-616 307 10 the the DET cana-616 307 11 policy policy NOUN cana-616 307 12 recommendations recommendation NOUN cana-616 307 13 from from ADP cana-616 307 14 the the DET cana-616 307 15 study study NOUN cana-616 307 16 done do VERB cana-616 307 17 have have VERB cana-616 307 18 a a DET cana-616 307 19 huge huge ADJ cana-616 307 20 bearing bearing NOUN cana-616 307 21 on on ADP cana-616 307 22 the the DET cana-616 307 23 government government NOUN cana-616 307 24 in in ADP cana-616 307 25 implementation implementation NOUN cana-616 307 26 of of ADP cana-616 307 27 laws law NOUN cana-616 307 28 that that PRON cana-616 307 29 govern govern VERB cana-616 307 30 animal animal NOUN cana-616 307 31 health health NOUN cana-616 307 32 sector sector NOUN cana-616 307 33 . . PUNCT cana-616 308 1 with with ADP cana-616 308 2 the the DET cana-616 308 3 help help NOUN cana-616 308 4 of of ADP cana-616 308 5 epidemiological epidemiological ADJ cana-616 308 6 methods method NOUN cana-616 308 7 such such ADJ cana-616 308 8 as as ADP cana-616 308 9 pinpointing pinpoint VERB cana-616 308 10 the the DET cana-616 308 11 main main ADJ cana-616 308 12 risk risk NOUN cana-616 308 13 factors factor NOUN cana-616 308 14 and and CCONJ cana-616 308 15 areas area NOUN cana-616 308 16 where where SCONJ cana-616 308 17 the the DET cana-616 308 18 disease disease NOUN cana-616 308 19 is be AUX cana-616 308 20 prevalent prevalent ADJ cana-616 308 21 the the DET cana-616 308 22 most most ADJ cana-616 308 23 , , PUNCT cana-616 308 24 policymakers policymaker NOUN cana-616 308 25 may may AUX cana-616 308 26 implement implement VERB cana-616 308 27 more more ADJ cana-616 308 28 and and CCONJ cana-616 308 29 more more ADV cana-616 308 30 successful successful ADJ cana-616 308 31 disease disease NOUN cana-616 308 32 control control NOUN cana-616 308 33 strategies strategy NOUN cana-616 308 34 . . PUNCT cana-616 309 1 such such ADJ cana-616 309 2 disparate disparate ADJ cana-616 309 3 measures measure NOUN cana-616 309 4 could could AUX cana-616 309 5 be be AUX cana-616 309 6 by by ADP cana-616 309 7 way way NOUN cana-616 309 8 of of ADP cana-616 309 9 vaccination vaccination NOUN cana-616 309 10 drives drive NOUN cana-616 309 11 in in ADP cana-616 309 12 those those DET cana-616 309 13 areas area NOUN cana-616 309 14 , , PUNCT cana-616 309 15 quarantine quarantine NOUN cana-616 309 16 regulations regulation NOUN cana-616 309 17 , , PUNCT cana-616 309 18 and and CCONJ cana-616 309 19 livestock livestock NOUN cana-616 309 20 movement movement NOUN cana-616 309 21 prohibition prohibition NOUN cana-616 309 22 between between ADP cana-616 309 23 counties county NOUN cana-616 309 24 to to PART cana-616 309 25 stop stop VERB cana-616 309 26 lsd lsd NOUN cana-616 309 27 from from ADP cana-616 309 28 spreading spread VERB cana-616 309 29 . . PUNCT cana-616 310 1 veterinary veterinary ADJ cana-616 310 2 practices practice NOUN cana-616 310 3 : : PUNCT cana-616 310 4 veterinarians veterinarian NOUN cana-616 310 5 and and CCONJ cana-616 310 6 cattle cattle NOUN cana-616 310 7 farmers farmer NOUN cana-616 310 8 can can AUX cana-616 310 9 utilize utilize VERB cana-616 310 10 the the DET cana-616 310 11 outcomes outcome NOUN cana-616 310 12 from from ADP cana-616 310 13 this this DET cana-616 310 14 study study NOUN cana-616 310 15 for for ADP cana-616 310 16 better well ADJ cana-616 310 17 diagnoses diagnosis NOUN cana-616 310 18 , , PUNCT cana-616 310 19 treatment treatment NOUN cana-616 310 20 regiments regiment NOUN cana-616 310 21 and and CCONJ cana-616 310 22 techniques technique NOUN cana-616 310 23 . . PUNCT cana-616 311 1 through through ADP cana-616 311 2 knowledge knowledge NOUN cana-616 311 3 of of ADP cana-616 311 4 the the DET cana-616 311 5 clinical clinical ADJ cana-616 311 6 symptoms symptom NOUN cana-616 311 7 and and CCONJ cana-616 311 8 risk risk NOUN cana-616 311 9 prediction prediction NOUN cana-616 311 10 factors factor NOUN cana-616 311 11 of of ADP cana-616 311 12 lsd lsd NOUN cana-616 311 13 there there PRON cana-616 311 14 could could AUX cana-616 311 15 be be AUX cana-616 311 16 a a DET cana-616 311 17 quicker quick ADJ cana-616 311 18 diagnosis diagnosis NOUN cana-616 311 19 and and CCONJ cana-616 311 20 more more ADV cana-616 311 21 focused focused ADJ cana-616 311 22 treatments treatment NOUN cana-616 311 23 , , PUNCT cana-616 311 24 reducing reduce VERB cana-616 311 25 morbidity morbidity NOUN cana-616 311 26 and and CCONJ cana-616 311 27 mortality mortality NOUN cana-616 311 28 standard standard NOUN cana-616 311 29 for for ADP cana-616 311 30 the the DET cana-616 311 31 illness illness NOUN cana-616 311 32 . . PUNCT cana-616 312 1 moreover moreover ADV cana-616 312 2 , , PUNCT cana-616 312 3 such such ADJ cana-616 312 4 models model NOUN cana-616 312 5 can can AUX cana-616 312 6 be be AUX cana-616 312 7 applied apply VERB cana-616 312 8 to to ADP cana-616 312 9 a a DET cana-616 312 10 livestock livestock NOUN cana-616 312 11 pathology pathology NOUN cana-616 312 12 monitoring monitoring NOUN cana-616 312 13 to to PART cana-616 312 14 facilitate facilitate VERB cana-616 312 15 prompt prompt ADJ cana-616 312 16 outbreak outbreak NOUN cana-616 312 17 detection detection NOUN cana-616 312 18 . . PUNCT cana-616 313 1 community community NOUN cana-616 313 2 engagement engagement NOUN cana-616 313 3 : : PUNCT cana-616 313 4 communities community NOUN cana-616 313 5 based base VERB cana-616 313 6 disease disease NOUN cana-616 313 7 control control NOUN cana-616 313 8 strategies strategy NOUN cana-616 313 9 are be AUX cana-616 313 10 essential essential ADJ cana-616 313 11 for for ADP cana-616 313 12 involving involve VERB cana-616 313 13 the the DET cana-616 313 14 local local ADJ cana-616 313 15 community community NOUN cana-616 313 16 . . PUNCT cana-616 314 1 education education NOUN cana-616 314 2 and and CCONJ cana-616 314 3 awareness awareness NOUN cana-616 314 4 campaigns campaign NOUN cana-616 314 5 will will AUX cana-616 314 6 tell tell VERB cana-616 314 7 the the DET cana-616 314 8 livestock livestock NOUN cana-616 314 9 farmers farmer NOUN cana-616 314 10 about about ADP cana-616 314 11 lsd lsd NOUN cana-616 314 12 symptoms symptom NOUN cana-616 314 13 , , PUNCT cana-616 314 14 the the DET cana-616 314 15 importance importance NOUN cana-616 314 16 of of ADP cana-616 314 17 timely timely ADV cana-616 314 18 going go VERB cana-616 314 19 to to ADP cana-616 314 20 the the DET cana-616 314 21 veterinarian veterinarian NOUN cana-616 314 22 clinic clinic NOUN cana-616 314 23 , , PUNCT cana-616 314 24 the the DET cana-616 314 25 efficient efficient ADJ cana-616 314 26 curing curing NOUN cana-616 314 27 and and CCONJ cana-616 314 28 prevention prevention NOUN cana-616 314 29 of of ADP cana-616 314 30 the the DET cana-616 314 31 disease disease NOUN cana-616 314 32 . . PUNCT cana-616 315 1 community community NOUN cana-616 315 2 - - PUNCT cana-616 315 3 based base VERB cana-616 315 4 methods method NOUN cana-616 315 5 have have VERB cana-616 315 6 the the DET cana-616 315 7 potential potential NOUN cana-616 315 8 to to PART cana-616 315 9 increase increase VERB cana-616 315 10 the the DET cana-616 315 11 impact impact NOUN cana-616 315 12 of of ADP cana-616 315 13 disease disease NOUN cana-616 315 14 control control VERB cana-616 315 15 inasmuch inasmuch ADJ cana-616 315 16 as as SCONJ cana-616 315 17 they they PRON cana-616 315 18 incorporate incorporate VERB cana-616 315 19 the the DET cana-616 315 20 determination determination NOUN cana-616 315 21 of of ADP cana-616 315 22 the the DET cana-616 315 23 population population NOUN cana-616 315 24 and and CCONJ cana-616 315 25 participation participation NOUN cana-616 315 26 of of ADP cana-616 315 27 all all DET cana-616 315 28 stakeholders stakeholder NOUN cana-616 315 29 in in ADP cana-616 315 30 livestock livestock NOUN cana-616 315 31 care care NOUN cana-616 315 32 . . PUNCT cana-616 316 1 conclusion conclusion NOUN cana-616 316 2 : : PUNCT cana-616 316 3 this this DET cana-616 316 4 research research NOUN cana-616 316 5 presents present VERB cana-616 316 6 a a DET cana-616 316 7 groundbreaking groundbreake VERB cana-616 316 8 advancement advancement NOUN cana-616 316 9 in in ADP cana-616 316 10 non non ADJ cana-616 316 11 - - ADJ cana-616 316 12 linear linear ADJ cana-616 316 13 classification classification NOUN cana-616 316 14 through through ADP cana-616 316 15 the the DET cana-616 316 16 introduction introduction NOUN cana-616 316 17 of of ADP cana-616 316 18 an an DET cana-616 316 19 enhanced enhance VERB cana-616 316 20 random random ADJ cana-616 316 21 forest forest NOUN cana-616 316 22 classifier classifier NOUN cana-616 316 23 . . PUNCT cana-616 317 1 by by ADP cana-616 317 2 leveraging leverage VERB cana-616 317 3 a a DET cana-616 317 4 novel novel ADJ cana-616 317 5 bayesian bayesian NOUN cana-616 317 6 optimization optimization NOUN cana-616 317 7 approach approach NOUN cana-616 317 8 that that PRON cana-616 317 9 integrates integrate VERB cana-616 317 10 gradient gradient NOUN cana-616 317 11 and and CCONJ cana-616 317 12 hessian hessian ADJ cana-616 317 13 computations computation NOUN cana-616 317 14 , , PUNCT cana-616 317 15 we we PRON cana-616 317 16 aimed aim VERB cana-616 317 17 to to PART cana-616 317 18 enhance enhance VERB cana-616 317 19 both both DET cana-616 317 20 communications communication NOUN cana-616 317 21 on on ADP cana-616 317 22 applied apply VERB cana-616 317 23 nonlinear nonlinear ADJ cana-616 317 24 analysis analysis NOUN cana-616 317 25 issn issn NOUN cana-616 317 26 : : PUNCT cana-616 317 27 1074 1074 NUM cana-616 317 28 - - PUNCT cana-616 317 29 133x 133x NUM cana-616 317 30 vol vol NOUN cana-616 317 31 31 31 NUM cana-616 317 32 no no NOUN cana-616 317 33 . . PUNCT cana-616 318 1 2s 2s NUM cana-616 318 2 ( ( PUNCT cana-616 318 3 2024 2024 NUM cana-616 318 4 ) ) PUNCT cana-616 318 5 143 143 NUM cana-616 318 6 https://internationalpubls.com https://internationalpubls.com X cana-616 318 7 the the DET cana-616 318 8 accuracy accuracy NOUN cana-616 318 9 and and CCONJ cana-616 318 10 computational computational ADJ cana-616 318 11 efficiency efficiency NOUN cana-616 318 12 of of ADP cana-616 318 13 the the DET cana-616 318 14 model model NOUN cana-616 318 15 , , PUNCT cana-616 318 16 particularly particularly ADV cana-616 318 17 when when SCONJ cana-616 318 18 applied apply VERB cana-616 318 19 to to ADP cana-616 318 20 image image NOUN cana-616 318 21 data datum NOUN cana-616 318 22 pertaining pertain VERB cana-616 318 23 to to PART cana-616 318 24 lumpy lumpy VERB cana-616 318 25 skin skin NOUN cana-616 318 26 disease disease NOUN cana-616 318 27 . . PUNCT cana-616 319 1 through through ADP cana-616 319 2 a a DET cana-616 319 3 rigorous rigorous ADJ cana-616 319 4 series series NOUN cana-616 319 5 of of ADP cana-616 319 6 experiments experiment NOUN cana-616 319 7 , , PUNCT cana-616 319 8 we we PRON cana-616 319 9 statistically statistically ADV cana-616 319 10 evaluated evaluate VERB cana-616 319 11 the the DET cana-616 319 12 performance performance NOUN cana-616 319 13 of of ADP cana-616 319 14 our our PRON cana-616 319 15 proposed propose VERB cana-616 319 16 classifier classifier NOUN cana-616 319 17 against against ADP cana-616 319 18 traditional traditional ADJ cana-616 319 19 models model NOUN cana-616 319 20 , , PUNCT cana-616 319 21 utilizing utilize VERB cana-616 319 22 a a DET cana-616 319 23 comprehensive comprehensive ADJ cana-616 319 24 dataset dataset NOUN cana-616 319 25 of of ADP cana-616 319 26 annotated annotate VERB cana-616 319 27 images image NOUN cana-616 319 28 depicting depict VERB cana-616 319 29 various various ADJ cana-616 319 30 disease disease NOUN cana-616 319 31 stages stage NOUN cana-616 319 32 . . PUNCT cana-616 320 1 our our PRON cana-616 320 2 results result NOUN cana-616 320 3 unequivocally unequivocally ADV cana-616 320 4 demonstrate demonstrate VERB cana-616 320 5 the the DET cana-616 320 6 superior superior ADJ cana-616 320 7 performance performance NOUN cana-616 320 8 of of ADP cana-616 320 9 our our PRON cana-616 320 10 model model NOUN cana-616 320 11 in in ADP cana-616 320 12 terms term NOUN cana-616 320 13 of of ADP cana-616 320 14 accuracy accuracy NOUN cana-616 320 15 , , PUNCT cana-616 320 16 sensitivity sensitivity NOUN cana-616 320 17 , , PUNCT cana-616 320 18 and and CCONJ cana-616 320 19 specificity specificity NOUN cana-616 320 20 . . PUNCT cana-616 321 1 crucially crucially ADV cana-616 321 2 , , PUNCT cana-616 321 3 bayesian bayesian NOUN cana-616 321 4 optimization optimization NOUN cana-616 321 5 played play VERB cana-616 321 6 a a DET cana-616 321 7 pivotal pivotal ADJ cana-616 321 8 role role NOUN cana-616 321 9 in in ADP cana-616 321 10 fine fine ADV cana-616 321 11 - - PUNCT cana-616 321 12 tuning tune VERB cana-616 321 13 the the DET cana-616 321 14 hyper hyper ADJ cana-616 321 15 parameters parameter NOUN cana-616 321 16 of of ADP cana-616 321 17 the the DET cana-616 321 18 classifier classifier NOUN cana-616 321 19 , , PUNCT cana-616 321 20 resulting result VERB cana-616 321 21 in in ADP cana-616 321 22 significant significant ADJ cana-616 321 23 improvements improvement NOUN cana-616 321 24 in in ADP cana-616 321 25 learning learn VERB cana-616 321 26 rates rate NOUN cana-616 321 27 and and CCONJ cana-616 321 28 decision decision NOUN cana-616 321 29 boundary boundary ADJ cana-616 321 30 formations formation NOUN cana-616 321 31 . . PUNCT cana-616 322 1 this this DET cana-616 322 2 optimization optimization NOUN cana-616 322 3 strategy strategy NOUN cana-616 322 4 not not PART cana-616 322 5 only only ADV cana-616 322 6 enhances enhance VERB cana-616 322 7 the the DET cana-616 322 8 model model NOUN cana-616 322 9 's 's PART cana-616 322 10 predictive predictive ADJ cana-616 322 11 capabilities capability NOUN cana-616 322 12 but but CCONJ cana-616 322 13 also also ADV cana-616 322 14 streamlines streamline VERB cana-616 322 15 computational computational ADJ cana-616 322 16 resources resource NOUN cana-616 322 17 , , PUNCT cana-616 322 18 making make VERB cana-616 322 19 it it PRON cana-616 322 20 a a DET cana-616 322 21 highly highly ADV cana-616 322 22 efficient efficient ADJ cana-616 322 23 tool tool NOUN cana-616 322 24 for for ADP cana-616 322 25 real real ADJ cana-616 322 26 - - PUNCT cana-616 322 27 world world NOUN cana-616 322 28 applications application NOUN cana-616 322 29 . . PUNCT cana-616 323 1 this this DET cana-616 323 2 paper paper NOUN cana-616 323 3 meticulously meticulously ADV cana-616 323 4 outlines outline VERB cana-616 323 5 our our PRON cana-616 323 6 methodology methodology NOUN cana-616 323 7 , , PUNCT cana-616 323 8 experimental experimental ADJ cana-616 323 9 setup setup NOUN cana-616 323 10 , , PUNCT cana-616 323 11 and and CCONJ cana-616 323 12 statistical statistical ADJ cana-616 323 13 validations validation NOUN cana-616 323 14 , , PUNCT cana-616 323 15 providing provide VERB cana-616 323 16 a a DET cana-616 323 17 comprehensive comprehensive ADJ cana-616 323 18 understanding understanding NOUN cana-616 323 19 of of ADP cana-616 323 20 our our PRON cana-616 323 21 approach approach NOUN cana-616 323 22 's 's PART cana-616 323 23 efficacy efficacy NOUN cana-616 323 24 . . PUNCT cana-616 324 1 importantly importantly ADV cana-616 324 2 , , PUNCT cana-616 324 3 our our PRON cana-616 324 4 findings finding NOUN cana-616 324 5 underscore underscore VERB cana-616 324 6 the the DET cana-616 324 7 potential potential NOUN cana-616 324 8 of of ADP cana-616 324 9 the the DET cana-616 324 10 improved improve VERB cana-616 324 11 random random ADJ cana-616 324 12 forest forest NOUN cana-616 324 13 classifier classifier NOUN cana-616 324 14 as as ADP cana-616 324 15 a a DET cana-616 324 16 potent potent ADJ cana-616 324 17 tool tool NOUN cana-616 324 18 for for ADP cana-616 324 19 veterinary veterinary ADJ cana-616 324 20 diagnostics diagnostic NOUN cana-616 324 21 , , PUNCT cana-616 324 22 particularly particularly ADV cana-616 324 23 in in ADP cana-616 324 24 the the DET cana-616 324 25 context context NOUN cana-616 324 26 of of ADP cana-616 324 27 lumpy lumpy ADJ cana-616 324 28 skin skin NOUN cana-616 324 29 disease disease NOUN cana-616 324 30 . . PUNCT cana-616 325 1 moreover moreover ADV cana-616 325 2 , , PUNCT cana-616 325 3 the the DET cana-616 325 4 adaptability adaptability NOUN cana-616 325 5 of of ADP cana-616 325 6 our our PRON cana-616 325 7 approach approach NOUN cana-616 325 8 suggests suggest VERB cana-616 325 9 broader broad ADJ cana-616 325 10 applicability applicability NOUN cana-616 325 11 across across ADP cana-616 325 12 diverse diverse ADJ cana-616 325 13 image image NOUN cana-616 325 14 classification classification NOUN cana-616 325 15 tasks task NOUN cana-616 325 16 , , PUNCT cana-616 325 17 promising promise VERB cana-616 325 18 advancements advancement NOUN cana-616 325 19 in in ADP cana-616 325 20 various various ADJ cana-616 325 21 fields field NOUN cana-616 325 22 beyond beyond ADP cana-616 325 23 veterinary veterinary ADJ cana-616 325 24 medicine medicine NOUN cana-616 325 25 . . PUNCT cana-616 326 1 overall overall ADV cana-616 326 2 , , PUNCT cana-616 326 3 our our PRON cana-616 326 4 research research NOUN cana-616 326 5 represents represent VERB cana-616 326 6 a a DET cana-616 326 7 significant significant ADJ cana-616 326 8 step step NOUN cana-616 326 9 forward forward ADV cana-616 326 10 in in ADP cana-616 326 11 harnessing harness VERB cana-616 326 12 machine machine NOUN cana-616 326 13 learning learn VERB cana-616 326 14 techniques technique NOUN cana-616 326 15 for for ADP cana-616 326 16 precise precise ADJ cana-616 326 17 and and CCONJ cana-616 326 18 efficient efficient ADJ cana-616 326 19 disease disease NOUN cana-616 326 20 diagnosis diagnosis NOUN cana-616 326 21 and and CCONJ cana-616 326 22 underscores underscore VERB cana-616 326 23 the the DET cana-616 326 24 transformative transformative ADJ cana-616 326 25 potential potential NOUN cana-616 326 26 of of ADP cana-616 326 27 bayesian bayesian NOUN cana-616 326 28 optimization optimization NOUN cana-616 326 29 in in ADP cana-616 326 30 optimizing optimize VERB cana-616 326 31 complex complex ADJ cana-616 326 32 classifiers classifier NOUN cana-616 326 33 . . PUNCT cana-616 327 1 references reference NOUN cana-616 327 2 [ [ X cana-616 327 3 1 1 NUM cana-616 327 4 ] ] X cana-616 327 5 şevik şevik PROPN cana-616 327 6 m m PROPN cana-616 327 7 , , PUNCT cana-616 327 8 avci avci PROPN cana-616 327 9 o o NOUN cana-616 327 10 , , PUNCT cana-616 327 11 doğan doğan PROPN cana-616 327 12 m m NOUN cana-616 327 13 , , PUNCT cana-616 327 14 iΜ‡nce iΜ‡nce NOUN cana-616 327 15 ΓΆb ΓΆb NOUN cana-616 327 16 β€œ " PUNCT cana-616 327 17 serum serum NOUN cana-616 327 18 biochemistry biochemistry NOUN cana-616 327 19 of of ADP cana-616 327 20 lumpy lumpy ADJ cana-616 327 21 skin skin NOUN cana-616 327 22 disease disease NOUN cana-616 327 23 virus virus NOUN cana-616 327 24 - - PUNCT cana-616 327 25 infected infect VERB cana-616 327 26 cattle cattle NOUN cana-616 327 27 . . PUNCT cana-616 327 28 biomed biome VERB cana-616 327 29 res re NOUN cana-616 327 30 int int NOUN cana-616 327 31 . . PUNCT cana-616 328 1 2016 2016 NUM cana-616 328 2 ; ; PUNCT cana-616 328 3 2016:6257984 2016:6257984 NUM cana-616 328 4 . . PUNCT cana-616 328 5 doi doi PROPN cana-616 328 6 : : PUNCT cana-616 328 7 10.1155/2016/6257984 10.1155/2016/6257984 PROPN cana-616 328 8 . . PUNCT cana-616 329 1 epub epub PROPN cana-616 329 2 ( ( PUNCT cana-616 329 3 2016 2016 NUM cana-616 329 4 ) ) PUNCT cana-616 329 5 may may AUX cana-616 329 6 12 12 NUM cana-616 329 7 . . PUNCT cana-616 330 1 pmid pmid NOUN cana-616 330 2 : : PUNCT cana-616 330 3 27294125 27294125 NUM cana-616 330 4 ; ; PUNCT cana-616 330 5 pmcid pmcid PROPN cana-616 330 6 : : PUNCT cana-616 330 7 pmc4880690 pmc4880690 NOUN cana-616 330 8 . . PUNCT cana-616 331 1 [ [ X cana-616 331 2 2 2 NUM cana-616 331 3 ] ] PUNCT cana-616 331 4 annandale annandale X cana-616 331 5 , , PUNCT cana-616 331 6 c c NOUN cana-616 331 7 h h NOUN cana-616 331 8 et et PROPN cana-616 331 9 al al PROPN cana-616 331 10 . . PUNCT cana-616 332 1 β€œ " PUNCT cana-616 332 2 seminal seminal ADJ cana-616 332 3 transmission transmission NOUN cana-616 332 4 of of ADP cana-616 332 5 lumpy lumpy ADJ cana-616 332 6 skin skin NOUN cana-616 332 7 disease disease NOUN cana-616 332 8 virus virus NOUN cana-616 332 9 in in ADP cana-616 332 10 heifers heifer NOUN cana-616 332 11 . . PUNCT cana-616 332 12 ” " PUNCT cana-616 333 1 transboundary transboundary ADJ cana-616 333 2 and and CCONJ cana-616 333 3 emerging emerge VERB cana-616 333 4 diseases disease NOUN cana-616 333 5 vol vol NOUN cana-616 333 6 . . PUNCT cana-616 334 1 61,5 61,5 PROPN cana-616 334 2 ( ( PUNCT cana-616 334 3 2014 2014 NUM cana-616 334 4 ): ): PUNCT cana-616 334 5 443 443 NUM cana-616 334 6 - - SYM cana-616 334 7 8 8 NUM cana-616 334 8 . . 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PUNCT cana-616 336 1 β€œ " PUNCT cana-616 336 2 outbreak outbreak NOUN cana-616 336 3 investigation investigation NOUN cana-616 336 4 and and CCONJ cana-616 336 5 molecular molecular ADJ cana-616 336 6 diagnosis diagnosis NOUN cana-616 336 7 of of ADP cana-616 336 8 lumpy lumpy ADJ cana-616 336 9 skin skin NOUN cana-616 336 10 disease disease NOUN cana-616 336 11 among among ADP cana-616 336 12 livestock livestock NOUN cana-616 336 13 in in ADP cana-616 336 14 saudi saudi PROPN cana-616 336 15 arabia arabia PROPN cana-616 336 16 ” " PUNCT cana-616 336 17 transboundary transboundary NOUN cana-616 336 18 and and CCONJ cana-616 336 19 emerging emerge VERB cana-616 336 20 diseases disease NOUN cana-616 336 21 vol vol NOUN cana-616 336 22 . . 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PUNCT cana-616 340 1 doi doi NOUN cana-616 340 2 : : PUNCT cana-616 340 3 10.15406 10.15406 NUM cana-616 340 4 / / SYM cana-616 340 5 jdvar.2018.07.00187 jdvar.2018.07.00187 PROPN cana-616 340 6 . . PUNCT cana-616 341 1 [ [ X cana-616 341 2 5 5 NUM cana-616 341 3 ] ] X cana-616 341 4 das das PROPN cana-616 341 5 m m PROPN cana-616 341 6 , , PUNCT cana-616 341 7 chowdhury chowdhury PROPN cana-616 341 8 ms ms PROPN cana-616 341 9 , , PUNCT cana-616 341 10 akter akter NOUN cana-616 341 11 s s PART cana-616 341 12 , , PUNCT cana-616 341 13 et et PROPN cana-616 341 14 al al PROPN cana-616 341 15 . . PUNCT cana-616 342 1 β€œ " PUNCT cana-616 342 2 an an DET cana-616 342 3 updated update VERB cana-616 342 4 review review NOUN cana-616 342 5 on on ADP cana-616 342 6 lumpy lumpy ADJ cana-616 342 7 skin skin NOUN cana-616 342 8 disease disease NOUN cana-616 342 9 : : PUNCT cana-616 342 10 perspective perspective NOUN cana-616 342 11 of of ADP cana-616 342 12 southeast southeast ADJ cana-616 342 13 asian asian ADJ cana-616 342 14 countries country NOUN cana-616 342 15 ” " PUNCT cana-616 342 16 , , PUNCT cana-616 342 17 journal journal NOUN cana-616 342 18 of of ADP cana-616 342 19 advanced advanced ADJ cana-616 342 20 biotechnology biotechnology NOUN cana-616 342 21 and and CCONJ cana-616 342 22 experimental experimental ADJ cana-616 342 23 therapeutics therapeutic NOUN cana-616 342 24 , , PUNCT cana-616 342 25 vol.4 vol.4 PROPN cana-616 342 26 , , PUNCT cana-616 342 27 pp pp X cana-616 342 28 . . 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PROPN cana-616 348 3 , , PUNCT cana-616 348 4 3(2 3(2 NUM cana-616 348 5 ) ) PUNCT cana-616 348 6 , , PUNCT cana-616 348 7 1–21 1–21 PROPN cana-616 348 8 , , PUNCT cana-616 348 9 2021 2021 NUM cana-616 348 10 , , PUNCT cana-616 348 11 doi doi NOUN cana-616 348 12 : : PUNCT cana-616 348 13 10.1007 10.1007 NUM cana-616 348 14 / / SYM cana-616 348 15 s42979 s42979 NOUN cana-616 348 16 - - PUNCT cana-616 348 17 021 021 NUM cana-616 348 18 - - PUNCT cana-616 348 19 00592 00592 NUM cana-616 348 20 - - PUNCT cana-616 348 21 x. x. NOUN cana-616 349 1 [ [ X cana-616 349 2 8 8 NUM cana-616 349 3 ] ] PUNCT cana-616 349 4 mujumdar mujumdar NOUN cana-616 349 5 , , PUNCT cana-616 349 6 a. a. PROPN cana-616 349 7 & & CCONJ cana-616 349 8 vaidehi vaidehi PROPN cana-616 349 9 , , PUNCT cana-616 349 10 v. v. 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PUNCT cana-616 354 1 sustain sustain VERB cana-616 354 2 . . PUNCT cana-616 355 1 dev dev PROPN cana-616 355 2 . . PUNCT cana-616 356 1 goals goal NOUN cana-616 356 2 , , PUNCT cana-616 356 3 1–6 1–6 NUM cana-616 356 4 , , PUNCT cana-616 356 5 doi doi NOUN cana-616 356 6 : : PUNCT cana-616 356 7 10.1109 10.1109 NUM cana-616 356 8 / / SYM cana-616 356 9 seb seb NOUN cana-616 356 10 - - PUNCT cana-616 356 11 sdg57117.2023.10124629 sdg57117.2023.10124629 NOUN cana-616 356 12 . . PUNCT cana-616 357 1 [ [ X cana-616 357 2 10 10 NUM cana-616 357 3 ] ] X cana-616 357 4 sobowale sobowale NOUN cana-616 357 5 , , PUNCT cana-616 357 6 a. a. NOUN cana-616 357 7 , , PUNCT cana-616 357 8 olaniyan olaniyan ADJ cana-616 357 9 , , PUNCT cana-616 357 10 o. o. NOUN cana-616 357 11 m. m. NOUN cana-616 357 12 , , PUNCT cana-616 357 13 adetan adetan ADJ cana-616 357 14 , , PUNCT cana-616 357 15 o. o. 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PROPN cana-616 358 2 , , PUNCT cana-616 358 3 3(5 3(5 NUM cana-616 358 4 ) ) PUNCT cana-616 358 5 , , PUNCT cana-616 358 6 895–900 895–900 NUM cana-616 358 7 , , PUNCT cana-616 358 8 2020 2020 NUM cana-616 358 9 . . PUNCT cana-616 359 1 communications communication NOUN cana-616 359 2 on on ADP cana-616 359 3 applied apply VERB cana-616 359 4 nonlinear nonlinear ADJ cana-616 359 5 analysis analysis NOUN cana-616 359 6 issn issn NOUN cana-616 359 7 : : PUNCT cana-616 359 8 1074 1074 NUM cana-616 359 9 - - PUNCT cana-616 359 10 133x 133x NUM cana-616 359 11 vol vol NOUN cana-616 359 12 31 31 NUM cana-616 359 13 no no NOUN cana-616 359 14 . . PUNCT cana-616 360 1 2s 2s NUM cana-616 360 2 ( ( PUNCT cana-616 360 3 2024 2024 NUM cana-616 360 4 ) ) PUNCT cana-616 360 5 144 144 NUM cana-616 360 6 https://internationalpubls.com https://internationalpubls.com X cana-616 361 1 [ [ X cana-616 361 2 11 11 NUM cana-616 361 3 ] ] X cana-616 361 4 arora arora PROPN cana-616 361 5 , , PUNCT cana-616 361 6 a. a. NOUN cana-616 361 7 β€œ " PUNCT cana-616 361 8 optimization optimization NOUN cana-616 361 9 of of ADP cana-616 361 10 state state NOUN cana-616 361 11 - - PUNCT cana-616 361 12 of of ADP cana-616 361 13 - - PUNCT cana-616 361 14 the the DET cana-616 361 15 - - PUNCT cana-616 361 16 art art NOUN cana-616 361 17 fuzzy fuzzy ADJ cana-616 361 18 - - PUNCT cana-616 361 19 metaheuristic metaheuristic ADJ cana-616 361 20 anfis anfis PROPN cana-616 361 21 - - PUNCT cana-616 361 22 based base VERB cana-616 361 23 machine machine NOUN cana-616 361 24 learning learning NOUN cana-616 361 25 models model NOUN cana-616 361 26 for for ADP cana-616 361 27 flood flood NOUN cana-616 361 28 susceptibility susceptibility NOUN cana-616 361 29 prediction prediction NOUN cana-616 361 30 mapping mapping NOUN cana-616 361 31 in in ADP cana-616 361 32 the the DET cana-616 361 33 middle middle PROPN cana-616 361 34 ganga ganga PROPN cana-616 361 35 plain plain PROPN cana-616 361 36 , , PUNCT cana-616 361 37 india india PROPN cana-616 361 38 . . PUNCT cana-616 362 1 sci sci PROPN cana-616 362 2 . . PROPN cana-616 362 3 total total ADJ cana-616 362 4 enviro enviro NOUN cana-616 362 5 ” " PUNCT cana-616 362 6 . . PUNCT cana-616 362 7 , , PUNCT cana-616 362 8 7(50 7(50 NUM cana-616 362 9 ) ) PUNCT cana-616 362 10 , , PUNCT cana-616 362 11 141 141 NUM cana-616 362 12 - - SYM cana-616 362 13 565 565 NUM cana-616 362 14 , , PUNCT cana-616 362 15 2020 2020 NUM cana-616 362 16 , , PUNCT cana-616 362 17 doi doi NOUN cana-616 362 18 : : PUNCT cana-616 362 19 10.1016 10.1016 NUM cana-616 362 20 / / SYM cana-616 362 21 j.scitotenv.2020.141565 j.scitotenv.2020.141565 NOUN cana-616 362 22 . . PUNCT cana-616 363 1 [ [ X cana-616 363 2 12 12 NUM cana-616 363 3 ] ] X cana-616 363 4 shen shen PROPN cana-616 363 5 , , PUNCT cana-616 363 6 z. z. PROPN cana-616 363 7 , , PUNCT cana-616 363 8 wu wu PROPN cana-616 363 9 , , PUNCT cana-616 363 10 q. q. PROPN cana-616 363 11 , , PUNCT cana-616 363 12 wang wang PROPN cana-616 363 13 , , PUNCT cana-616 363 14 z. z. PROPN cana-616 363 15 , , PUNCT cana-616 363 16 chen chen PROPN cana-616 363 17 , , PUNCT cana-616 363 18 g. g. PROPN cana-616 363 19 & & CCONJ cana-616 363 20 lin lin PROPN cana-616 363 21 , , PUNCT cana-616 363 22 g. g. PROPN cana-616 364 1 β€œ " PUNCT cana-616 364 2 diabetic diabetic ADJ cana-616 364 3 retinopathy retinopathy ADJ cana-616 364 4 prediction prediction NOUN cana-616 364 5 by by ADP cana-616 364 6 ensemble ensemble ADJ cana-616 364 7 learning learning NOUN cana-616 364 8 based base VERB cana-616 364 9 on on ADP cana-616 364 10 biochemical biochemical ADJ cana-616 364 11 and and CCONJ cana-616 364 12 physical physical ADJ cana-616 364 13 data datum NOUN cana-616 364 14 ” " PUNCT cana-616 364 15 . . PUNCT cana-616 365 1 sensors sensor NOUN cana-616 365 2 , , PUNCT cana-616 365 3 1–19 1–19 NOUN cana-616 365 4 , , PUNCT cana-616 365 5 2021 2021 NUM cana-616 365 6 , , PUNCT cana-616 365 7 [ [ X cana-616 365 8 13 13 NUM cana-616 365 9 ] ] SYM cana-616 365 10 alazzam alazzam PROPN cana-616 365 11 , , PUNCT cana-616 365 12 m. m. PROPN cana-616 365 13 b. b. PROPN cana-616 365 14 , , PUNCT cana-616 365 15 alassery alassery PROPN cana-616 365 16 , , PUNCT cana-616 365 17 f. f. PROPN cana-616 365 18 & & CCONJ cana-616 365 19 almulihi almulihi PROPN cana-616 365 20 , , PUNCT cana-616 365 21 a a DET cana-616 365 22 β€œ " PUNCT cana-616 365 23 identification identification NOUN cana-616 365 24 of of ADP cana-616 365 25 diabetic diabetic ADJ cana-616 365 26 retinopathy retinopathy NOUN cana-616 365 27 through through ADP cana-616 365 28 machine machine NOUN cana-616 365 29 learning learning NOUN cana-616 365 30 . . PUNCT cana-616 366 1 mob mob NOUN cana-616 366 2 . . PUNCT cana-616 366 3 inf inf PROPN cana-616 366 4 . . PUNCT cana-616 366 5 syst syst PROPN cana-616 366 6 . . PUNCT cana-616 366 7 ” " PUNCT cana-616 366 8 , , PUNCT cana-616 366 9 2021 2021 NUM cana-616 366 10 , , PUNCT cana-616 366 11 doi doi NOUN cana-616 366 12 : : PUNCT cana-616 366 13 10.1155/2021/1155116 10.1155/2021/1155116 NUM cana-616 366 14 . . PUNCT cana-616 367 1 [ [ X cana-616 367 2 14 14 NUM cana-616 367 3 ] ] X cana-616 367 4 batta batta PROPN cana-616 367 5 , , PUNCT cana-616 367 6 m. m. NOUN cana-616 367 7 β€œ " PUNCT cana-616 367 8 machine machine NOUN cana-616 367 9 learning learning NOUN cana-616 367 10 algorithms algorithm VERB cana-616 367 11 a a DET cana-616 367 12 review review NOUN cana-616 367 13 . . PUNCT cana-616 368 1 int int NOUN cana-616 368 2 . . PUNCT cana-616 369 1 j. j. PROPN cana-616 369 2 sci sci PROPN cana-616 369 3 . . PUNCT cana-616 370 1 res res PROPN cana-616 370 2 . . PROPN cana-616 370 3 , , PUNCT cana-616 370 4 8(18 8(18 NUM cana-616 370 5 ) ) PUNCT cana-616 370 6 , , PUNCT cana-616 370 7 381–386 381–386 NUM cana-616 370 8 , , PUNCT cana-616 370 9 2018 2018 NUM cana-616 370 10 , , PUNCT cana-616 370 11 doi doi NOUN cana-616 370 12 : : PUNCT cana-616 370 13 10.21275 10.21275 NUM cana-616 370 14 / / SYM cana-616 370 15 art20203995 art20203995 ADV cana-616 370 16 . . PUNCT cana-616 371 1 [ [ X cana-616 371 2 15 15 NUM cana-616 371 3 ] ] X cana-616 371 4 madhavan madhavan PROPN cana-616 371 5 , , PUNCT cana-616 371 6 m. m. NOUN cana-616 371 7 v. v. PROPN cana-616 371 8 , , PUNCT cana-616 371 9 pande pande NOUN cana-616 371 10 , , PUNCT cana-616 371 11 s. s. PROPN cana-616 371 12 , , PUNCT cana-616 371 13 umekar umekar NOUN cana-616 371 14 , , PUNCT cana-616 371 15 p. p. PROPN cana-616 371 16 , , PUNCT cana-616 371 17 mahore mahore PROPN cana-616 371 18 , , PUNCT cana-616 371 19 t. t. PROPN cana-616 371 20 & & CCONJ cana-616 371 21 kalyankar kalyankar PROPN cana-616 371 22 , , PUNCT cana-616 371 23 d d NOUN cana-616 371 24 β€œ " PUNCT cana-616 371 25 comparative comparative ADJ cana-616 371 26 analysis analysis NOUN cana-616 371 27 of of ADP cana-616 371 28 detection detection NOUN cana-616 371 29 of of ADP cana-616 371 30 email email NOUN cana-616 371 31 spam spam NOUN cana-616 371 32 with with ADP cana-616 371 33 the the DET cana-616 371 34 aid aid NOUN cana-616 371 35 of of ADP cana-616 371 36 machine machine NOUN cana-616 371 37 learning learning NOUN cana-616 371 38 approaches approach NOUN cana-616 371 39 ” " PUNCT cana-616 371 40 iop iop NOUN cana-616 371 41 conf conf NOUN cana-616 371 42 . . PUNCT cana-616 372 1 ser ser PROPN cana-616 372 2 . . PUNCT cana-616 373 1 mater mater PROPN cana-616 373 2 . . PUNCT cana-616 374 1 sci sci PROPN cana-616 374 2 . . PUNCT cana-616 375 1 eng eng PROPN cana-616 375 2 . . PROPN cana-616 375 3 , , PUNCT cana-616 375 4 2021 2021 NUM cana-616 375 5 , , PUNCT cana-616 375 6 doi doi NOUN cana-616 375 7 : : PUNCT cana-616 375 8 10.1088/1757 10.1088/1757 NUM cana-616 375 9 899x/1022/1/012113 899x/1022/1/012113 NUM cana-616 375 10 . . PUNCT cana-616 376 1 [ [ X cana-616 376 2 16 16 NUM cana-616 376 3 ] ] X cana-616 376 4 sethi sethi PROPN cana-616 376 5 , , PUNCT cana-616 376 6 c. c. PROPN cana-616 376 7 c. c. PROPN cana-616 376 8 β€œ " PUNCT cana-616 376 9 e e NOUN cana-616 376 10 - - NOUN cana-616 376 11 mail mail NOUN cana-616 376 12 spam spam NOUN cana-616 376 13 detection detection NOUN cana-616 376 14 using use VERB cana-616 376 15 machine machine NOUN cana-616 376 16 learning learning NOUN cana-616 376 17 and and CCONJ cana-616 376 18 deep deep ADJ cana-616 376 19 learning learning NOUN cana-616 376 20 ” " PUNCT cana-616 376 21 , , PUNCT cana-616 376 22 int int PROPN cana-616 376 23 . . PUNCT cana-616 377 1 j. j. PROPN cana-616 377 2 res res PROPN cana-616 377 3 . . PUNCT cana-616 378 1 appl appl PROPN cana-616 378 2 . . PUNCT cana-616 379 1 sci sci PROPN cana-616 379 2 . . PUNCT cana-616 380 1 eng eng PROPN cana-616 380 2 . . PROPN cana-616 381 1 technol technol PROPN cana-616 381 2 . . PROPN cana-616 381 3 , , PUNCT cana-616 381 4 6(8 6(8 NUM cana-616 381 5 ) ) PUNCT cana-616 381 6 , , PUNCT cana-616 381 7 981–985 981–985 NUM cana-616 381 8 , , PUNCT cana-616 381 9 2020 2020 NUM cana-616 381 10 , , PUNCT cana-616 381 11 doi doi NOUN cana-616 381 12 : : PUNCT cana-616 381 13 10.22214 10.22214 NUM cana-616 381 14 / / SYM cana-616 381 15 ijraset.2020.6159 ijraset.2020.6159 NOUN cana-616 381 16 . . PUNCT cana-616 382 1 [ [ X cana-616 382 2 17 17 NUM cana-616 382 3 ] ] X cana-616 382 4 yile yile NOUN cana-616 382 5 , , PUNCT cana-616 382 6 a. a. NOUN cana-616 382 7 o. o. PROPN cana-616 382 8 , , PUNCT cana-616 382 9 hongqi hongqi NOUN cana-616 382 10 , , PUNCT cana-616 382 11 l. l. PROPN cana-616 382 12 , , PUNCT cana-616 382 13 liping liping PROPN cana-616 382 14 , , PUNCT cana-616 382 15 z. z. PROPN cana-616 382 16 , , PUNCT cana-616 382 17 sikandar sikandar PROPN cana-616 382 18 , , PUNCT cana-616 382 19 a. a. PROPN cana-616 382 20 & & CCONJ cana-616 382 21 zhongguo zhongguo PROPN cana-616 382 22 , , PUNCT cana-616 382 23 y. y. PROPN cana-616 382 24 β€œ " PUNCT cana-616 382 25 the the DET cana-616 382 26 linear linear ADJ cana-616 382 27 random random ADJ cana-616 382 28 forest forest NOUN cana-616 382 29 algorithm algorithm NOUN cana-616 382 30 and and CCONJ cana-616 382 31 its its PRON cana-616 382 32 advantages advantage NOUN cana-616 382 33 in in ADP cana-616 382 34 machine machine NOUN cana-616 382 35 learning learning NOUN cana-616 382 36 assisted assist VERB cana-616 382 37 logging log VERB cana-616 382 38 regression regression NOUN cana-616 382 39 modeling modeling NOUN cana-616 382 40 ” " PUNCT cana-616 382 41 , , PUNCT cana-616 382 42 j. j. PROPN cana-616 382 43 pet pet PROPN cana-616 382 44 . . PUNCT cana-616 383 1 sci sci PROPN cana-616 383 2 . . PUNCT cana-616 384 1 eng eng PROPN cana-616 384 2 . . PROPN cana-616 384 3 , , PUNCT cana-616 384 4 4(17 4(17 NUM cana-616 384 5 ) ) PUNCT cana-616 384 6 , , PUNCT cana-616 384 7 776–789 776–789 NUM cana-616 384 8 , , PUNCT cana-616 384 9 2019 2019 NUM cana-616 384 10 , , PUNCT cana-616 384 11 doi doi NOUN cana-616 384 12 : : PUNCT cana-616 384 13 10.1016 10.1016 NUM cana-616 384 14 / / SYM cana-616 384 15 j.petrol.2018.11.067 j.petrol.2018.11.067 PROPN cana-616 384 16 . . PUNCT cana-616 385 1 [ [ X cana-616 385 2 18 18 NUM cana-616 385 3 ] ] SYM cana-616 385 4 ali ali PROPN cana-616 385 5 , , PUNCT cana-616 385 6 a. a. PROPN cana-616 385 7 , , PUNCT cana-616 385 8 ahmed ahmed PROPN cana-616 385 9 , , PUNCT cana-616 385 10 m. m. NOUN cana-616 385 11 , , PUNCT cana-616 385 12 naeem naeem PROPN cana-616 385 13 , , PUNCT cana-616 385 14 s. s. PROPN cana-616 385 15 , , PUNCT cana-616 385 16 anam anam PROPN cana-616 385 17 , , PUNCT cana-616 385 18 s. s. PROPN cana-616 385 19 & & CCONJ cana-616 385 20 ahmed ahmed PROPN cana-616 385 21 , , PUNCT cana-616 385 22 m. m. NOUN cana-616 385 23 m. m. NOUN cana-616 385 24 β€œ " PUNCT cana-616 385 25 an an DET cana-616 385 26 unsupervised unsupervised ADJ cana-616 385 27 machine machine NOUN cana-616 385 28 learning learning NOUN cana-616 385 29 algorithms algorithm NOUN cana-616 385 30 : : PUNCT cana-616 385 31 comprehensive comprehensive ADJ cana-616 385 32 review review PROPN cana-616 385 33 ” " PUNCT cana-616 385 34 , , PUNCT cana-616 385 35 int int NOUN cana-616 385 36 . . PUNCT cana-616 386 1 j. j. PROPN cana-616 386 2 comput comput PROPN cana-616 386 3 . . PUNCT cana-616 387 1 digit digit PROPN cana-616 387 2 . . PUNCT cana-616 388 1 syst syst PROPN cana-616 388 2 . . PUNCT cana-616 388 3 , , PUNCT cana-616 388 4 2(20 2(20 NUM cana-616 388 5 ) ) PUNCT cana-616 388 6 , , PUNCT cana-616 388 7 210–242 210–242 NUM cana-616 388 8 , , PUNCT cana-616 388 9 2023 2023 NUM cana-616 388 10 , , PUNCT cana-616 388 11 doi doi NOUN cana-616 388 12 : : PUNCT cana-616 388 13 10.12785 10.12785 NUM cana-616 388 14 / / SYM cana-616 388 15 ijcds/130172 ijcds/130172 NOUN cana-616 388 16 . . PUNCT cana-616 389 1 [ [ X cana-616 389 2 19 19 NUM cana-616 389 3 ] ] PUNCT cana-616 389 4 bakumenko bakumenko NOUN cana-616 389 5 , , PUNCT cana-616 389 6 a. a. NOUN cana-616 389 7 & & CCONJ cana-616 389 8 elragal elragal PROPN cana-616 389 9 , , PUNCT cana-616 389 10 a. a. NOUN cana-616 389 11 β€œ " PUNCT cana-616 389 12 detecting detect VERB cana-616 389 13 anomalies anomaly NOUN cana-616 389 14 in in ADP cana-616 389 15 financial financial ADJ cana-616 389 16 data datum NOUN cana-616 389 17 using use VERB cana-616 389 18 machine machine NOUN cana-616 389 19 learning learning NOUN cana-616 389 20 algorithms algorithm NOUN cana-616 389 21 . . PUNCT cana-616 390 1 systems system NOUN cana-616 390 2 ” " PUNCT cana-616 390 3 , , PUNCT cana-616 390 4 5(10 5(10 NUM cana-616 390 5 ) ) PUNCT cana-616 390 6 , , PUNCT cana-616 390 7 32 32 NUM cana-616 390 8 - - SYM cana-616 390 9 48 48 NUM cana-616 390 10 , , PUNCT cana-616 390 11 2022 2022 NUM cana-616 390 12 , , PUNCT cana-616 390 13 doi doi NOUN cana-616 390 14 : : PUNCT cana-616 390 15 10.3390 10.3390 NUM cana-616 390 16 / / SYM cana-616 390 17 systems10050130 systems10050130 PROPN cana-616 390 18 . . PUNCT cana-616 391 1 [ [ X cana-616 391 2 20 20 NUM cana-616 391 3 ] ] SYM cana-616 391 4 reddy reddy NOUN cana-616 391 5 , , PUNCT cana-616 391 6 p. p. NOUN cana-616 391 7 , , PUNCT cana-616 391 8 viswanath viswanath NOUN cana-616 391 9 , , PUNCT cana-616 391 10 p. p. PROPN cana-616 391 11 & & CCONJ cana-616 391 12 reddy reddy PROPN cana-616 391 13 , , PUNCT cana-616 391 14 e. e. PROPN cana-616 391 15 b. b. PROPN cana-616 392 1 β€œ " PUNCT cana-616 392 2 semi semi ADJ cana-616 392 3 - - ADJ cana-616 392 4 supervised supervised ADJ cana-616 392 5 learning learning NOUN cana-616 392 6 : : PUNCT cana-616 392 7 a a DET cana-616 392 8 brief brief ADJ cana-616 392 9 review review NOUN cana-616 392 10 ” " PUNCT cana-616 392 11 . . PUNCT cana-616 393 1 int int NOUN cana-616 393 2 . . PUNCT cana-616 394 1 j. j. PROPN cana-616 394 2 eng eng PROPN cana-616 394 3 . . PROPN cana-616 395 1 technol technol PROPN cana-616 395 2 . . PROPN cana-616 395 3 , , PUNCT cana-616 395 4 18(7 18(7 NUM cana-616 395 5 ) ) PUNCT cana-616 395 6 , , PUNCT cana-616 395 7 118 118 NUM cana-616 395 8 , , PUNCT cana-616 395 9 2018 2018 NUM cana-616 395 10 , , PUNCT cana-616 395 11 doi doi NOUN cana-616 395 12 : : PUNCT cana-616 395 13 10.14419 10.14419 NUM cana-616 395 14 / / SYM cana-616 395 15 ijet.v7i1.8.9977 ijet.v7i1.8.9977 ADJ cana-616 395 16 . . PUNCT cana-616 396 1 [ [ X cana-616 396 2 21 21 NUM cana-616 396 3 ] ] X cana-616 396 4 singh singh PROPN cana-616 396 5 , , PUNCT cana-616 396 6 v. v. PROPN cana-616 396 7 , , PUNCT cana-616 396 8 chen chen PROPN cana-616 396 9 , , PUNCT cana-616 396 10 s. s. PROPN cana-616 396 11 s. s. PROPN cana-616 396 12 , , PUNCT cana-616 396 13 singhania singhania PROPN cana-616 396 14 , , PUNCT cana-616 396 15 b. b. PROPN cana-616 396 16 nanavati nanavati PROPN cana-616 396 17 , , PUNCT cana-616 396 18 a. a. NOUN cana-616 396 19 kumarkar kumarkar PROPN cana-616 396 20 , , PUNCT cana-616 396 21 & & CCONJ cana-616 396 22 gupta gupta PROPN cana-616 396 23 , , PUNCT cana-616 396 24 a. a. NOUN cana-616 396 25 β€œ " PUNCT cana-616 396 26 how how SCONJ cana-616 396 27 are be AUX cana-616 396 28 reinforcement reinforcement NOUN cana-616 396 29 learning learning NOUN cana-616 396 30 and and CCONJ cana-616 396 31 deep deep ADJ cana-616 396 32 learning learning NOUN cana-616 396 33 algorithms algorithm NOUN cana-616 396 34 used use VERB cana-616 396 35 for for ADP cana-616 396 36 big big ADJ cana-616 396 37 data datum NOUN cana-616 396 38 based base VERB cana-616 396 39 decision decision NOUN cana-616 396 40 making make VERB cana-616 396 41 in in ADP cana-616 396 42 financial financial ADJ cana-616 396 43 industries industry NOUN cana-616 396 44 – – PUNCT cana-616 396 45 a a DET cana-616 396 46 review review NOUN cana-616 396 47 and and CCONJ cana-616 396 48 research research NOUN cana-616 396 49 agenda agenda NOUN cana-616 396 50 . . PUNCT cana-616 397 1 int int NOUN cana-616 397 2 . . PUNCT cana-616 398 1 j. j. PROPN cana-616 398 2 inf inf PROPN cana-616 398 3 . . PROPN cana-616 398 4 manag manag PROPN cana-616 398 5 . . PUNCT cana-616 399 1 data datum NOUN cana-616 399 2 insights insight NOUN cana-616 399 3 , , PUNCT cana-616 399 4 2(2 2(2 NUM cana-616 399 5 ) ) PUNCT cana-616 399 6 , , PUNCT cana-616 399 7 100 100 NUM cana-616 399 8 109 109 NUM cana-616 399 9 , , PUNCT cana-616 399 10 2022 2022 NUM cana-616 399 11 , , PUNCT cana-616 399 12 doi doi NOUN cana-616 399 13 : : PUNCT cana-616 399 14 10.1016 10.1016 NUM cana-616 399 15 / / SYM cana-616 399 16 j.jjimei.2022.100094 j.jjimei.2022.100094 NOUN cana-616 399 17 . . PUNCT cana-616 400 1 [ [ X cana-616 400 2 22 22 NUM cana-616 400 3 ] ] SYM cana-616 400 4 yang yang PROPN cana-616 400 5 , , PUNCT cana-616 400 6 c. c. PROPN cana-616 400 7 ; ; PUNCT cana-616 400 8 wang wang PROPN cana-616 400 9 , , PUNCT cana-616 400 10 y. y. PROPN cana-616 400 11 ; ; PUNCT cana-616 400 12 zhang zhang PROPN cana-616 400 13 , , PUNCT cana-616 400 14 a. a. PROPN cana-616 400 15 ; ; PUNCT cana-616 400 16 fan fan PROPN cana-616 400 17 , , PUNCT cana-616 400 18 h. h. PROPN cana-616 400 19 ; ; PUNCT cana-616 400 20 guo guo PROPN cana-616 400 21 , , PUNCT cana-616 400 22 l. l. PROPN cana-616 400 23 a a DET cana-616 400 24 random random ADJ cana-616 400 25 forest forest NOUN cana-616 400 26 algorithm algorithm NOUN cana-616 400 27 combined combine VERB cana-616 400 28 with with ADP cana-616 400 29 bayesian bayesian NOUN cana-616 400 30 optimization optimization NOUN cana-616 400 31 for for ADP cana-616 400 32 atmospheric atmospheric ADJ cana-616 400 33 duct duct NOUN cana-616 400 34 estimation estimation NOUN cana-616 400 35 . . PUNCT cana-616 401 1 remote remote PROPN cana-616 401 2 sens sen NOUN cana-616 401 3 . . PROPN cana-616 401 4 2023 2023 NUM cana-616 401 5 , , PUNCT cana-616 401 6 15 15 NUM cana-616 401 7 , , PUNCT cana-616 401 8 4296 4296 NUM cana-616 401 9 . . PUNCT cana-616 402 1 https://doi.org/10.3390/rs15174296 https://doi.org/10.3390/rs15174296 X cana-616 402 2 . . PUNCT cana-616 403 1 [ [ X cana-616 403 2 23 23 NUM cana-616 403 3 ] ] PUNCT cana-616 403 4 j. j. PROPN cana-616 403 5 m. m. PROPN cana-616 403 6 bofill bofill PROPN cana-616 403 7 , , PUNCT cana-616 403 8 β€œ " PUNCT cana-616 403 9 updated update VERB cana-616 403 10 hessian hessian ADJ cana-616 403 11 matrix matrix NOUN cana-616 403 12 and and CCONJ cana-616 403 13 the the DET cana-616 403 14 restricted restricted ADJ cana-616 403 15 step step NOUN cana-616 403 16 method method NOUN cana-616 403 17 for for ADP cana-616 403 18 locating locate VERB cana-616 403 19 transition transition NOUN cana-616 403 20 structures structure NOUN cana-616 403 21 , , PUNCT cana-616 403 22 ” " PUNCT cana-616 403 23 j. j. PROPN cana-616 403 24 comput comput PROPN cana-616 403 25 . . PUNCT cana-616 404 1 chem chem NOUN cana-616 404 2 . . PUNCT cana-616 405 1 15 15 NUM cana-616 405 2 , , PUNCT cana-616 405 3 1–11 1–11 PROPN cana-616 405 4 ( ( PUNCT cana-616 405 5 1994 1994 NUM cana-616 405 6 ) ) PUNCT cana-616 405 7 . . PUNCT cana-616 406 1 [ [ X cana-616 406 2 24 24 NUM cana-616 406 3 ] ] X cana-616 406 4 h. h. PROPN cana-616 406 5 li li PROPN cana-616 406 6 and and CCONJ cana-616 406 7 j. j. PROPN cana-616 406 8 h. h. PROPN cana-616 406 9 jensen jensen PROPN cana-616 406 10 , , PUNCT cana-616 406 11 β€œ " PUNCT cana-616 406 12 partial partial ADJ cana-616 406 13 hessian hessian ADJ cana-616 406 14 vibrational vibrational ADJ cana-616 406 15 analysis analysis NOUN cana-616 406 16 : : PUNCT cana-616 406 17 the the DET cana-616 406 18 localization localization NOUN cana-616 406 19 of of ADP cana-616 406 20 the the DET cana-616 406 21 molecular molecular ADJ cana-616 406 22 vibrational vibrational ADJ cana-616 406 23 energy energy NOUN cana-616 406 24 and and CCONJ cana-616 406 25 entropy entropy NOUN cana-616 406 26 , , PUNCT cana-616 406 27 ” " PUNCT cana-616 406 28 theor theor PROPN cana-616 406 29 . . PUNCT cana-616 407 1 chem chem PROPN cana-616 407 2 . . PUNCT cana-616 408 1 acc acc PROPN cana-616 408 2 . . PROPN cana-616 408 3 107 107 NUM cana-616 408 4 , , PUNCT cana-616 408 5 211–219 211–219 NUM cana-616 408 6 ( ( PUNCT cana-616 408 7 2002 2002 NUM cana-616 408 8 ) ) PUNCT cana-616 408 9 . . PUNCT cana-616 409 1 [ [ X cana-616 409 2 25 25 NUM cana-616 409 3 ] ] PUNCT cana-616 409 4 h. h. PROPN cana-616 409 5 wu wu PROPN cana-616 409 6 , , PUNCT cana-616 409 7 m. m. PROPN cana-616 409 8 rahman rahman PROPN cana-616 409 9 , , PUNCT cana-616 409 10 j. j. PROPN cana-616 409 11 wang wang PROPN cana-616 409 12 , , PUNCT cana-616 409 13 u. u. PROPN cana-616 409 14 louderaj louderaj PROPN cana-616 409 15 , , PUNCT cana-616 409 16 w. w. PROPN cana-616 409 17 l. l. PROPN cana-616 409 18 hase hase PROPN cana-616 409 19 , , PUNCT cana-616 409 20 and and CCONJ cana-616 409 21 y. y. PROPN cana-616 409 22 zhuang zhuang PROPN cana-616 409 23 , , PUNCT cana-616 409 24 β€œ " PUNCT cana-616 409 25 higher high ADJ cana-616 409 26 - - PUNCT cana-616 409 27 accuracy accuracy NOUN cana-616 409 28 schemes scheme NOUN cana-616 409 29 for for ADP cana-616 409 30 approximating approximate VERB cana-616 409 31 the the DET cana-616 409 32 hessian hessian NOUN cana-616 409 33 from from ADP cana-616 409 34 electronic electronic ADJ cana-616 409 35 structure structure NOUN cana-616 409 36 calculations calculation NOUN cana-616 409 37 in in ADP cana-616 409 38 chemical chemical ADJ cana-616 409 39 dynamics dynamic NOUN cana-616 409 40 simulations simulation NOUN cana-616 409 41 , , PUNCT cana-616 409 42 ” " PUNCT cana-616 409 43 j. j. PROPN cana-616 409 44 chem chem PROPN cana-616 409 45 . . PUNCT cana-616 410 1 phys phy NOUN cana-616 410 2 . . PUNCT cana-616 411 1 133 133 NUM cana-616 411 2 , , PUNCT cana-616 411 3 074101 074101 NUM cana-616 411 4 , , PUNCT cana-616 411 5 ( ( PUNCT cana-616 411 6 2010 2010 NUM cana-616 411 7 ) ) PUNCT cana-616 411 8 . . PUNCT cana-616 412 1 [ [ X cana-616 412 2 26 26 NUM cana-616 412 3 ] ] PUNCT cana-616 412 4 m. m. NOUN cana-616 412 5 ceotto ceotto NOUN cana-616 412 6 , , PUNCT cana-616 412 7 y. y. PROPN cana-616 412 8 zhuang zhuang PROPN cana-616 412 9 , , PUNCT cana-616 412 10 and and CCONJ cana-616 412 11 w. w. PROPN cana-616 412 12 l. l. PROPN cana-616 412 13 hase hase PROPN cana-616 412 14 , , PUNCT cana-616 412 15 β€œ " PUNCT cana-616 412 16 accelerated accelerate VERB cana-616 412 17 direct direct ADJ cana-616 412 18 semiclassical semiclassical ADJ cana-616 412 19 molecular molecular ADJ cana-616 412 20 dynamics dynamic NOUN cana-616 412 21 using use VERB cana-616 412 22 a a DET cana-616 412 23 compact compact ADJ cana-616 412 24 finite finite ADJ cana-616 412 25 difference difference NOUN cana-616 412 26 hessian hessian NOUN cana-616 412 27 scheme scheme NOUN cana-616 412 28 , , PUNCT cana-616 412 29 ” " PUNCT cana-616 412 30 j. j. PROPN cana-616 412 31 chem chem PROPN cana-616 412 32 . . PUNCT cana-616 413 1 phys phy NOUN cana-616 413 2 . . PUNCT cana-616 414 1 138 138 NUM cana-616 414 2 , , PUNCT cana-616 414 3 054116 054116 NUM cana-616 414 4 , , PUNCT cana-616 414 5 ( ( PUNCT cana-616 414 6 2013 2013 NUM cana-616 414 7 ) ) PUNCT cana-616 414 8 . . PUNCT