id sid tid token lemma pos fbem-594 1 1 frontiers frontier NOUN fbem-594 1 2 in in ADP fbem-594 1 3 business business NOUN fbem-594 1 4 , , PUNCT fbem-594 1 5 economics economic NOUN fbem-594 1 6 and and CCONJ fbem-594 1 7 management management NOUN fbem-594 1 8 issn issn PROPN fbem-594 1 9 : : PUNCT fbem-594 1 10 2766 2766 NUM fbem-594 1 11 - - PUNCT fbem-594 1 12 824x 824x NUM fbem-594 1 13 | | ADJ fbem-594 1 14 vol vol NOUN fbem-594 1 15 . . PROPN fbem-594 2 1 4 4 NUM fbem-594 2 2 , , PUNCT fbem-594 2 3 no no INTJ fbem-594 2 4 . . NOUN fbem-594 2 5 2 2 NUM fbem-594 2 6 , , PUNCT fbem-594 2 7 2022 2022 NUM fbem-594 2 8 1 1 NUM fbem-594 2 9 direction direction NOUN fbem-594 2 10 prediction prediction NOUN fbem-594 2 11 of of ADP fbem-594 2 12 traffic traffic NOUN fbem-594 2 13 flow flow NOUN fbem-594 2 14 in in ADP fbem-594 2 15 vissim vissim PROPN fbem-594 2 16 simulation simulation NOUN fbem-594 2 17 based base VERB fbem-594 2 18 on on ADP fbem-594 2 19 k k PROPN fbem-594 2 20 nearest near ADJ fbem-594 2 21 neighbor neighbor PROPN fbem-594 2 22 algorithm algorithm PROPN fbem-594 2 23 fuchao fuchao PROPN fbem-594 2 24 geng geng PROPN fbem-594 2 25 , , PUNCT fbem-594 2 26 yufan yufan PROPN fbem-594 2 27 ren ren PROPN fbem-594 2 28 school school NOUN fbem-594 2 29 of of ADP fbem-594 2 30 energy energy NOUN fbem-594 2 31 science science NOUN fbem-594 2 32 and and CCONJ fbem-594 2 33 engineering engineering NOUN fbem-594 2 34 , , PUNCT fbem-594 2 35 henan henan PROPN fbem-594 2 36 polytechnic polytechnic PROPN fbem-594 2 37 university university PROPN fbem-594 2 38 , , PUNCT fbem-594 2 39 jiaozuo jiaozuo PROPN fbem-594 2 40 454002 454002 NUM fbem-594 2 41 , , PUNCT fbem-594 2 42 china china PROPN fbem-594 2 43 abstract abstract NOUN fbem-594 2 44 : : PUNCT fbem-594 2 45 in in ADP fbem-594 2 46 order order NOUN fbem-594 2 47 to to PART fbem-594 2 48 make make VERB fbem-594 2 49 short short ADJ fbem-594 2 50 - - PUNCT fbem-594 2 51 term term NOUN fbem-594 2 52 prediction prediction NOUN fbem-594 2 53 of of ADP fbem-594 2 54 the the DET fbem-594 2 55 direction direction NOUN fbem-594 2 56 of of ADP fbem-594 2 57 traffic traffic NOUN fbem-594 2 58 flow flow NOUN fbem-594 2 59 in in ADP fbem-594 2 60 urban urban ADJ fbem-594 2 61 roads road NOUN fbem-594 2 62 , , PUNCT fbem-594 2 63 a a DET fbem-594 2 64 short short ADJ fbem-594 2 65 - - PUNCT fbem-594 2 66 term term NOUN fbem-594 2 67 prediction prediction NOUN fbem-594 2 68 method method NOUN fbem-594 2 69 of of ADP fbem-594 2 70 urban urban ADJ fbem-594 2 71 road road NOUN fbem-594 2 72 travel travel NOUN fbem-594 2 73 time time NOUN fbem-594 2 74 based base VERB fbem-594 2 75 on on ADP fbem-594 2 76 k k PROPN fbem-594 2 77 nearest near ADJ fbem-594 2 78 neighbor neighbor NOUN fbem-594 2 79 algorithm algorithm PROPN fbem-594 2 80 and and CCONJ fbem-594 2 81 vissim vissim PROPN fbem-594 2 82 simulation simulation NOUN fbem-594 2 83 is be AUX fbem-594 2 84 constructed construct VERB fbem-594 2 85 . . PUNCT fbem-594 3 1 first first ADV fbem-594 3 2 , , PUNCT fbem-594 3 3 the the DET fbem-594 3 4 intersection intersection NOUN fbem-594 3 5 of of ADP fbem-594 3 6 shiji shiji PROPN fbem-594 3 7 road road NOUN fbem-594 3 8 and and CCONJ fbem-594 3 9 yingbin yingbin PROPN fbem-594 3 10 road road NOUN fbem-594 3 11 was be AUX fbem-594 3 12 selected select VERB fbem-594 3 13 as as ADP fbem-594 3 14 the the DET fbem-594 3 15 survey survey NOUN fbem-594 3 16 site site NOUN fbem-594 3 17 , , PUNCT fbem-594 3 18 and and CCONJ fbem-594 3 19 the the DET fbem-594 3 20 number number NOUN fbem-594 3 21 of of ADP fbem-594 3 22 vehicles vehicle NOUN fbem-594 3 23 in in ADP fbem-594 3 24 each each DET fbem-594 3 25 direction direction NOUN fbem-594 3 26 of of ADP fbem-594 3 27 each each DET fbem-594 3 28 entrance entrance NOUN fbem-594 3 29 lane lane NOUN fbem-594 3 30 of of ADP fbem-594 3 31 the the DET fbem-594 3 32 intersection intersection NOUN fbem-594 3 33 was be AUX fbem-594 3 34 investigated investigate VERB fbem-594 3 35 using use VERB fbem-594 3 36 manual manual ADJ fbem-594 3 37 counting counting NOUN fbem-594 3 38 , , PUNCT fbem-594 3 39 and and CCONJ fbem-594 3 40 the the DET fbem-594 3 41 signal signal ADJ fbem-594 3 42 timing timing NOUN fbem-594 3 43 of of ADP fbem-594 3 44 each each DET fbem-594 3 45 phase phase NOUN fbem-594 3 46 of of ADP fbem-594 3 47 the the DET fbem-594 3 48 intersection intersection NOUN fbem-594 3 49 was be AUX fbem-594 3 50 investigated investigate VERB fbem-594 3 51 . . PUNCT fbem-594 4 1 input input VERB fbem-594 4 2 the the DET fbem-594 4 3 survey survey NOUN fbem-594 4 4 data datum NOUN fbem-594 4 5 into into ADP fbem-594 4 6 the the DET fbem-594 4 7 vissim vissim PROPN fbem-594 4 8 simulation simulation PROPN fbem-594 4 9 software software PROPN fbem-594 4 10 to to PART fbem-594 4 11 get get VERB fbem-594 4 12 the the DET fbem-594 4 13 travel travel NOUN fbem-594 4 14 time time NOUN fbem-594 4 15 of of ADP fbem-594 4 16 each each DET fbem-594 4 17 entrance entrance NOUN fbem-594 4 18 lane lane NOUN fbem-594 4 19 in in ADP fbem-594 4 20 each each DET fbem-594 4 21 direction direction NOUN fbem-594 4 22 . . PUNCT fbem-594 5 1 then then ADV fbem-594 5 2 build build VERB fbem-594 5 3 a a DET fbem-594 5 4 vissim vissim NOUN fbem-594 5 5 simulation simulation NOUN fbem-594 5 6 traffic traffic NOUN fbem-594 5 7 flow flow NOUN fbem-594 5 8 direction direction NOUN fbem-594 5 9 prediction prediction NOUN fbem-594 5 10 model model NOUN fbem-594 5 11 based base VERB fbem-594 5 12 on on ADP fbem-594 5 13 the the DET fbem-594 5 14 knn knn PROPN fbem-594 5 15 algorithm algorithm PROPN fbem-594 5 16 , , PUNCT fbem-594 5 17 including include VERB fbem-594 5 18 the the DET fbem-594 5 19 construction construction NOUN fbem-594 5 20 of of ADP fbem-594 5 21 feature feature NOUN fbem-594 5 22 vectors vector NOUN fbem-594 5 23 , , PUNCT fbem-594 5 24 cross cross ADJ fbem-594 5 25 - - ADJ fbem-594 5 26 validation validation ADJ fbem-594 5 27 methods method NOUN fbem-594 5 28 to to PART fbem-594 5 29 determine determine VERB fbem-594 5 30 k k PROPN fbem-594 5 31 values value NOUN fbem-594 5 32 , , PUNCT fbem-594 5 33 and and CCONJ fbem-594 5 34 local local ADJ fbem-594 5 35 estimation estimation NOUN fbem-594 5 36 methods method NOUN fbem-594 5 37 . . PUNCT fbem-594 6 1 the the DET fbem-594 6 2 experimental experimental ADJ fbem-594 6 3 results result NOUN fbem-594 6 4 show show VERB fbem-594 6 5 that that SCONJ fbem-594 6 6 the the DET fbem-594 6 7 average average ADJ fbem-594 6 8 relative relative ADJ fbem-594 6 9 error error NOUN fbem-594 6 10 between between ADP fbem-594 6 11 the the DET fbem-594 6 12 predicted predict VERB fbem-594 6 13 traffic traffic NOUN fbem-594 6 14 flow flow NOUN fbem-594 6 15 direction direction NOUN fbem-594 6 16 and and CCONJ fbem-594 6 17 the the DET fbem-594 6 18 actual actual ADJ fbem-594 6 19 traffic traffic NOUN fbem-594 6 20 flow flow NOUN fbem-594 6 21 direction direction NOUN fbem-594 6 22 tends tend VERB fbem-594 6 23 to to ADP fbem-594 6 24 0.27 0.27 NUM fbem-594 6 25 . . PUNCT fbem-594 7 1 due due ADP fbem-594 7 2 to to ADP fbem-594 7 3 the the DET fbem-594 7 4 small small ADJ fbem-594 7 5 amount amount NOUN fbem-594 7 6 of of ADP fbem-594 7 7 data datum NOUN fbem-594 7 8 , , PUNCT fbem-594 7 9 the the DET fbem-594 7 10 prediction prediction NOUN fbem-594 7 11 result result NOUN fbem-594 7 12 is be AUX fbem-594 7 13 more more ADV fbem-594 7 14 accurate accurate ADJ fbem-594 7 15 . . PUNCT fbem-594 8 1 keywords keyword NOUN fbem-594 8 2 : : PUNCT fbem-594 8 3 k k PROPN fbem-594 8 4 nearest near ADJ fbem-594 8 5 neighbor neighbor NOUN fbem-594 8 6 algorithm algorithm PROPN fbem-594 8 7 , , PUNCT fbem-594 8 8 vissim vissim PROPN fbem-594 8 9 simulation simulation NOUN fbem-594 8 10 , , PUNCT fbem-594 8 11 direction direction NOUN fbem-594 8 12 of of ADP fbem-594 8 13 traffic traffic NOUN fbem-594 8 14 flow flow NOUN fbem-594 8 15 . . PUNCT fbem-594 9 1 1 1 X fbem-594 9 2 . . X fbem-594 9 3 introduction introduction NOUN fbem-594 9 4 with with ADP fbem-594 9 5 the the DET fbem-594 9 6 economic economic ADJ fbem-594 9 7 and and CCONJ fbem-594 9 8 social social ADJ fbem-594 9 9 development development NOUN fbem-594 9 10 , , PUNCT fbem-594 9 11 the the DET fbem-594 9 12 number number NOUN fbem-594 9 13 of of ADP fbem-594 9 14 cars car NOUN fbem-594 9 15 in in ADP fbem-594 9 16 large large ADJ fbem-594 9 17 and and CCONJ fbem-594 9 18 medium medium ADJ fbem-594 9 19 - - PUNCT fbem-594 9 20 sized sized ADJ fbem-594 9 21 cities city NOUN fbem-594 9 22 in in ADP fbem-594 9 23 china china PROPN fbem-594 9 24 began begin VERB fbem-594 9 25 to to PART fbem-594 9 26 rise rise VERB fbem-594 9 27 sharply sharply ADV fbem-594 9 28 in in ADP fbem-594 9 29 recent recent ADJ fbem-594 9 30 years year NOUN fbem-594 9 31 , , PUNCT fbem-594 9 32 and and CCONJ fbem-594 9 33 the the DET fbem-594 9 34 resulting result VERB fbem-594 9 35 environmental environmental ADJ fbem-594 9 36 pollution pollution NOUN fbem-594 9 37 , , PUNCT fbem-594 9 38 traffic traffic NOUN fbem-594 9 39 accidents accident NOUN fbem-594 9 40 , , PUNCT fbem-594 9 41 especially especially ADV fbem-594 9 42 traffic traffic NOUN fbem-594 9 43 congestion congestion NOUN fbem-594 9 44 , , PUNCT fbem-594 9 45 are be AUX fbem-594 9 46 becoming become VERB fbem-594 9 47 more more ADV fbem-594 9 48 and and CCONJ fbem-594 9 49 more more ADV fbem-594 9 50 serious serious ADJ fbem-594 10 1 [ [ X fbem-594 10 2 1 1 NUM fbem-594 10 3 ] ] PUNCT fbem-594 10 4 . . PUNCT fbem-594 11 1 the the DET fbem-594 11 2 development development NOUN fbem-594 11 3 of of ADP fbem-594 11 4 intelligent intelligent ADJ fbem-594 11 5 transportation transportation NOUN fbem-594 11 6 system system NOUN fbem-594 11 7 is be AUX fbem-594 11 8 one one NUM fbem-594 11 9 of of ADP fbem-594 11 10 the the DET fbem-594 11 11 effective effective ADJ fbem-594 11 12 methods method NOUN fbem-594 11 13 to to PART fbem-594 11 14 solve solve VERB fbem-594 11 15 the the DET fbem-594 11 16 problems problem NOUN fbem-594 11 17 of of ADP fbem-594 11 18 urban urban ADJ fbem-594 11 19 road road NOUN fbem-594 11 20 traffic traffic NOUN fbem-594 11 21 congestion congestion NOUN fbem-594 11 22 and and CCONJ fbem-594 11 23 environmental environmental ADJ fbem-594 11 24 pollution pollution NOUN fbem-594 11 25 [ [ X fbem-594 11 26 2 2 NUM fbem-594 11 27 ] ] PUNCT fbem-594 11 28 . . PUNCT fbem-594 12 1 as as ADP fbem-594 12 2 an an DET fbem-594 12 3 important important ADJ fbem-594 12 4 research research NOUN fbem-594 12 5 field field NOUN fbem-594 12 6 of of ADP fbem-594 12 7 intelligent intelligent ADJ fbem-594 12 8 transportation transportation NOUN fbem-594 12 9 system system NOUN fbem-594 12 10 , , PUNCT fbem-594 12 11 urban urban ADJ fbem-594 12 12 road road NOUN fbem-594 12 13 traffic traffic NOUN fbem-594 12 14 flow flow NOUN fbem-594 12 15 direction direction NOUN fbem-594 12 16 prediction prediction NOUN fbem-594 12 17 can can AUX fbem-594 12 18 realize realize VERB fbem-594 12 19 traffic traffic NOUN fbem-594 12 20 guidance guidance NOUN fbem-594 12 21 and and CCONJ fbem-594 12 22 effectively effectively ADV fbem-594 12 23 alleviate alleviate VERB fbem-594 12 24 the the DET fbem-594 12 25 traffic traffic NOUN fbem-594 12 26 congestion congestion NOUN fbem-594 12 27 of of ADP fbem-594 12 28 urban urban ADJ fbem-594 12 29 roads road NOUN fbem-594 12 30 . . PUNCT fbem-594 13 1 the the DET fbem-594 13 2 data data NOUN fbem-594 13 3 sources source NOUN fbem-594 13 4 of of ADP fbem-594 13 5 research research NOUN fbem-594 13 6 related relate VERB fbem-594 13 7 to to ADP fbem-594 13 8 short short ADJ fbem-594 13 9 - - PUNCT fbem-594 13 10 term term NOUN fbem-594 13 11 traffic traffic NOUN fbem-594 13 12 flow flow NOUN fbem-594 13 13 prediction prediction NOUN fbem-594 13 14 mainly mainly ADV fbem-594 13 15 include include VERB fbem-594 13 16 gps gps NOUN fbem-594 13 17 floating float VERB fbem-594 13 18 car car NOUN fbem-594 13 19 data[3 data[3 NOUN fbem-594 13 20 - - SYM fbem-594 13 21 4 4 NUM fbem-594 13 22 ] ] PUNCT fbem-594 13 23 , , PUNCT fbem-594 13 24 fixed fixed ADJ fbem-594 13 25 loop loop NOUN fbem-594 13 26 detector detector NOUN fbem-594 13 27 data[5 data[5 NOUN fbem-594 13 28 ] ] PUNCT fbem-594 13 29 and and CCONJ fbem-594 13 30 vehicle vehicle NOUN fbem-594 13 31 electronic electronic ADJ fbem-594 13 32 identification identification NOUN fbem-594 13 33 data datum NOUN fbem-594 13 34 . . PUNCT fbem-594 14 1 however however ADV fbem-594 14 2 , , PUNCT fbem-594 14 3 at at ADP fbem-594 14 4 present present ADJ fbem-594 14 5 , , PUNCT fbem-594 14 6 the the DET fbem-594 14 7 short short ADJ fbem-594 14 8 - - PUNCT fbem-594 14 9 term term NOUN fbem-594 14 10 prediction prediction NOUN fbem-594 14 11 of of ADP fbem-594 14 12 travel travel NOUN fbem-594 14 13 time time NOUN fbem-594 14 14 at at ADP fbem-594 14 15 home home NOUN fbem-594 14 16 and and CCONJ fbem-594 14 17 abroad abroad ADV fbem-594 14 18 mostly mostly ADV fbem-594 14 19 focuses focus VERB fbem-594 14 20 on on ADP fbem-594 14 21 the the DET fbem-594 14 22 data datum NOUN fbem-594 14 23 based base VERB fbem-594 14 24 on on ADP fbem-594 14 25 gps gps PROPN fbem-594 14 26 floating float VERB fbem-594 14 27 car car NOUN fbem-594 14 28 and and CCONJ fbem-594 14 29 fixed fix VERB fbem-594 14 30 loop loop NOUN fbem-594 14 31 detector detector NOUN fbem-594 14 32 . . PUNCT fbem-594 15 1 gps gps PROPN fbem-594 15 2 floating float VERB fbem-594 15 3 car car NOUN fbem-594 15 4 only only ADV fbem-594 15 5 includes include VERB fbem-594 15 6 taxi taxi NOUN fbem-594 15 7 and and CCONJ fbem-594 15 8 bus bus NOUN fbem-594 15 9 data datum NOUN fbem-594 15 10 , , PUNCT fbem-594 15 11 but but CCONJ fbem-594 15 12 does do AUX fbem-594 15 13 not not PART fbem-594 15 14 include include VERB fbem-594 15 15 a a DET fbem-594 15 16 large large ADJ fbem-594 15 17 number number NOUN fbem-594 15 18 of of ADP fbem-594 15 19 private private ADJ fbem-594 15 20 car car NOUN fbem-594 15 21 travel travel NOUN fbem-594 15 22 data datum NOUN fbem-594 15 23 , , PUNCT fbem-594 15 24 it it PRON fbem-594 15 25 has have VERB fbem-594 15 26 the the DET fbem-594 15 27 disadvantage disadvantage NOUN fbem-594 15 28 of of ADP fbem-594 15 29 small small ADJ fbem-594 15 30 sample sample NOUN fbem-594 15 31 size size NOUN fbem-594 15 32 . . PUNCT fbem-594 16 1 the the DET fbem-594 16 2 fixed fix VERB fbem-594 16 3 loop loop NOUN fbem-594 16 4 detector detector NOUN fbem-594 16 5 is be AUX fbem-594 16 6 usually usually ADV fbem-594 16 7 only only ADV fbem-594 16 8 deployed deploy VERB fbem-594 16 9 at at ADP fbem-594 16 10 the the DET fbem-594 16 11 intersection intersection NOUN fbem-594 16 12 , , PUNCT fbem-594 16 13 which which PRON fbem-594 16 14 does do AUX fbem-594 16 15 not not PART fbem-594 16 16 have have VERB fbem-594 16 17 the the DET fbem-594 16 18 characteristics characteristic NOUN fbem-594 16 19 of of ADP fbem-594 16 20 universality universality NOUN fbem-594 16 21 in in ADP fbem-594 16 22 space space NOUN fbem-594 16 23 . . PUNCT fbem-594 17 1 for for ADP fbem-594 17 2 the the DET fbem-594 17 3 vehicle vehicle NOUN fbem-594 17 4 electronic electronic ADJ fbem-594 17 5 identification identification NOUN fbem-594 17 6 data datum NOUN fbem-594 17 7 , , PUNCT fbem-594 17 8 it it PRON fbem-594 17 9 is be AUX fbem-594 17 10 mostly mostly ADV fbem-594 17 11 used use VERB fbem-594 17 12 in in ADP fbem-594 17 13 the the DET fbem-594 17 14 related related ADJ fbem-594 17 15 research research NOUN fbem-594 17 16 of of ADP fbem-594 17 17 short short ADJ fbem-594 17 18 - - PUNCT fbem-594 17 19 term term NOUN fbem-594 17 20 traffic traffic NOUN fbem-594 17 21 flow flow NOUN fbem-594 17 22 prediction prediction NOUN fbem-594 17 23 , , PUNCT fbem-594 17 24 which which PRON fbem-594 17 25 has have VERB fbem-594 17 26 a a DET fbem-594 17 27 certain certain ADJ fbem-594 17 28 novelty novelty NOUN fbem-594 17 29 . . PUNCT fbem-594 18 1 at at ADP fbem-594 18 2 the the DET fbem-594 18 3 same same ADJ fbem-594 18 4 time time NOUN fbem-594 18 5 , , PUNCT fbem-594 18 6 because because SCONJ fbem-594 18 7 it it PRON fbem-594 18 8 includes include VERB fbem-594 18 9 the the DET fbem-594 18 10 travel travel NOUN fbem-594 18 11 data datum NOUN fbem-594 18 12 of of ADP fbem-594 18 13 all all DET fbem-594 18 14 vehicles vehicle NOUN fbem-594 18 15 , , PUNCT fbem-594 18 16 including include VERB fbem-594 18 17 private private ADJ fbem-594 18 18 cars car NOUN fbem-594 18 19 , , PUNCT fbem-594 18 20 it it PRON fbem-594 18 21 has have VERB fbem-594 18 22 the the DET fbem-594 18 23 advantage advantage NOUN fbem-594 18 24 of of ADP fbem-594 18 25 large large ADJ fbem-594 18 26 sample sample NOUN fbem-594 18 27 size size NOUN fbem-594 18 28 and and CCONJ fbem-594 18 29 extensive extensive ADJ fbem-594 18 30 spatial spatial ADJ fbem-594 18 31 distribution distribution NOUN fbem-594 18 32 . . PUNCT fbem-594 19 1 the the DET fbem-594 19 2 methods method NOUN fbem-594 19 3 of of ADP fbem-594 19 4 short short ADJ fbem-594 19 5 - - PUNCT fbem-594 19 6 term term NOUN fbem-594 19 7 traffic traffic NOUN fbem-594 19 8 prediction prediction NOUN fbem-594 19 9 mainly mainly ADV fbem-594 19 10 include include VERB fbem-594 19 11 linear linear PROPN fbem-594 19 12 regression regression NOUN fbem-594 19 13 model model NOUN fbem-594 19 14 , , PUNCT fbem-594 19 15 time time PROPN fbem-594 19 16 series series PROPN fbem-594 19 17 model model PROPN fbem-594 19 18 , , PUNCT fbem-594 19 19 kalman kalman PROPN fbem-594 19 20 filtering filtering PROPN fbem-594 19 21 model model PROPN fbem-594 19 22 , , PUNCT fbem-594 19 23 neural neural ADJ fbem-594 19 24 network network NOUN fbem-594 19 25 model model NOUN fbem-594 19 26 , , PUNCT fbem-594 19 27 nonparammetric nonparammetric ADJ fbem-594 19 28 regression regression NOUN fbem-594 19 29 model model NOUN fbem-594 19 30 , , PUNCT fbem-594 19 31 etc etc X fbem-594 19 32 . . X fbem-594 19 33 compared compare VERB fbem-594 19 34 with with ADP fbem-594 19 35 the the DET fbem-594 19 36 above above ADJ fbem-594 19 37 methods method NOUN fbem-594 19 38 , , PUNCT fbem-594 19 39 the the DET fbem-594 19 40 main main ADJ fbem-594 19 41 advantage advantage NOUN fbem-594 19 42 of of ADP fbem-594 19 43 k k NOUN fbem-594 19 44 - - PUNCT fbem-594 19 45 nearest near ADJ fbem-594 19 46 neighbor neighbor NOUN fbem-594 19 47 ( ( PUNCT fbem-594 19 48 knn knn PROPN fbem-594 19 49 ) ) PUNCT fbem-594 19 50 algorithm algorithm NOUN fbem-594 19 51 is be AUX fbem-594 19 52 that that SCONJ fbem-594 19 53 there there PRON fbem-594 19 54 is be VERB fbem-594 19 55 no no DET fbem-594 19 56 complex complex ADJ fbem-594 19 57 parameter parameter NOUN fbem-594 19 58 estimation estimation NOUN fbem-594 19 59 and and CCONJ fbem-594 19 60 the the DET fbem-594 19 61 model model NOUN fbem-594 19 62 training training NOUN fbem-594 19 63 time time NOUN fbem-594 19 64 is be AUX fbem-594 19 65 short short ADJ fbem-594 19 66 , , PUNCT fbem-594 19 67 it it PRON fbem-594 19 68 is be AUX fbem-594 19 69 suitable suitable ADJ fbem-594 19 70 for for ADP fbem-594 19 71 processing process VERB fbem-594 19 72 a a DET fbem-594 19 73 small small ADJ fbem-594 19 74 amount amount NOUN fbem-594 19 75 of of ADP fbem-594 19 76 data datum NOUN fbem-594 19 77 to to PART fbem-594 19 78 realize realize VERB fbem-594 19 79 real real ADJ fbem-594 19 80 - - PUNCT fbem-594 19 81 time time NOUN fbem-594 19 82 prediction prediction NOUN fbem-594 19 83 . . PUNCT fbem-594 20 1 at at ADP fbem-594 20 2 present present ADJ fbem-594 20 3 , , PUNCT fbem-594 20 4 knn knn PROPN fbem-594 20 5 algorithm algorithm PROPN fbem-594 20 6 has have AUX fbem-594 20 7 been be AUX fbem-594 20 8 applied apply VERB fbem-594 20 9 to to ADP fbem-594 20 10 short short ADJ fbem-594 20 11 - - PUNCT fbem-594 20 12 term term NOUN fbem-594 20 13 traffic traffic NOUN fbem-594 20 14 flow flow NOUN fbem-594 20 15 prediction prediction NOUN fbem-594 20 16 in in ADP fbem-594 20 17 literature literature NOUN fbem-594 20 18 . . PUNCT fbem-594 21 1 shlim shlim PROPN fbem-594 21 2 et et PROPN fbem-594 21 3 al[6 al[6 PROPN fbem-594 21 4 ] ] PUNCT fbem-594 21 5 used use VERB fbem-594 21 6 highway highway NOUN fbem-594 21 7 toll toll NOUN fbem-594 21 8 data datum NOUN fbem-594 21 9 to to PART fbem-594 21 10 apply apply VERB fbem-594 21 11 knn knn PROPN fbem-594 21 12 algorithm algorithm PROPN fbem-594 21 13 to to ADP fbem-594 21 14 real real ADJ fbem-594 21 15 - - PUNCT fbem-594 21 16 time time NOUN fbem-594 21 17 prediction prediction NOUN fbem-594 21 18 of of ADP fbem-594 21 19 travel travel NOUN fbem-594 21 20 time time NOUN fbem-594 21 21 . . PUNCT fbem-594 22 1 steve steve PROPN fbem-594 22 2 robinson robinson PROPN fbem-594 22 3 et et PROPN fbem-594 22 4 al[5 al[5 PROPN fbem-594 22 5 ] ] PUNCT fbem-594 22 6 proposed propose VERB fbem-594 22 7 the the DET fbem-594 22 8 strategy strategy NOUN fbem-594 22 9 of of ADP fbem-594 22 10 selecting select VERB fbem-594 22 11 local local ADJ fbem-594 22 12 estimation estimation NOUN fbem-594 22 13 method method NOUN fbem-594 22 14 and and CCONJ fbem-594 22 15 k k PROPN fbem-594 22 16 value value NOUN fbem-594 22 17 in in ADP fbem-594 22 18 knn knn PROPN fbem-594 22 19 algorithm algorithm PROPN fbem-594 22 20 , , PUNCT fbem-594 22 21 and and CCONJ fbem-594 22 22 carried carry VERB fbem-594 22 23 out out ADP fbem-594 22 24 experimental experimental ADJ fbem-594 22 25 analysis analysis NOUN fbem-594 22 26 on on ADP fbem-594 22 27 the the DET fbem-594 22 28 proposed propose VERB fbem-594 22 29 strategy strategy NOUN fbem-594 22 30 . . PUNCT fbem-594 23 1 in in ADP fbem-594 23 2 conclusion conclusion NOUN fbem-594 23 3 , , PUNCT fbem-594 23 4 it it PRON fbem-594 23 5 can can AUX fbem-594 23 6 be be AUX fbem-594 23 7 found find VERB fbem-594 23 8 that that SCONJ fbem-594 23 9 most most ADJ fbem-594 23 10 of of ADP fbem-594 23 11 the the DET fbem-594 23 12 existing exist VERB fbem-594 23 13 studies study NOUN fbem-594 23 14 are be AUX fbem-594 23 15 the the DET fbem-594 23 16 prediction prediction NOUN fbem-594 23 17 of of ADP fbem-594 23 18 travel travel NOUN fbem-594 23 19 time time NOUN fbem-594 23 20 based base VERB fbem-594 23 21 on on ADP fbem-594 23 22 gps gps PROPN fbem-594 23 23 floating float VERB fbem-594 23 24 vehicle vehicle NOUN fbem-594 23 25 data datum NOUN fbem-594 23 26 and and CCONJ fbem-594 23 27 fixed fix VERB fbem-594 23 28 ring ring NOUN fbem-594 23 29 coil coil NOUN fbem-594 23 30 detection detection NOUN fbem-594 23 31 data datum NOUN fbem-594 23 32 , , PUNCT fbem-594 23 33 and and CCONJ fbem-594 23 34 there there PRON fbem-594 23 35 is be VERB fbem-594 23 36 little little ADJ fbem-594 23 37 research research NOUN fbem-594 23 38 on on ADP fbem-594 23 39 the the DET fbem-594 23 40 prediction prediction NOUN fbem-594 23 41 of of ADP fbem-594 23 42 vehicle vehicle NOUN fbem-594 23 43 flow flow NOUN fbem-594 23 44 direction direction NOUN fbem-594 23 45 . . PUNCT fbem-594 24 1 based base VERB fbem-594 24 2 on on ADP fbem-594 24 3 this this PRON fbem-594 24 4 , , PUNCT fbem-594 24 5 this this DET fbem-594 24 6 paper paper NOUN fbem-594 24 7 predicts predict VERB fbem-594 24 8 the the DET fbem-594 24 9 direction direction NOUN fbem-594 24 10 of of ADP fbem-594 24 11 intersection intersection NOUN fbem-594 24 12 traffic traffic NOUN fbem-594 24 13 flow flow NOUN fbem-594 24 14 based base VERB fbem-594 24 15 on on ADP fbem-594 24 16 knn knn PROPN fbem-594 24 17 algorithm algorithm PROPN fbem-594 24 18 , , PUNCT fbem-594 24 19 based base VERB fbem-594 24 20 on on ADP fbem-594 24 21 the the DET fbem-594 24 22 actual actual ADJ fbem-594 24 23 home home NOUN fbem-594 24 24 socket socket NOUN fbem-594 24 25 traffic traffic NOUN fbem-594 24 26 flow flow NOUN fbem-594 24 27 data datum NOUN fbem-594 24 28 and and CCONJ fbem-594 24 29 vissim vissim PROPN fbem-594 24 30 simulation simulation PROPN fbem-594 24 31 software software PROPN fbem-594 24 32 . . PUNCT fbem-594 25 1 2 2 X fbem-594 25 2 . . X fbem-594 25 3 data datum NOUN fbem-594 25 4 survey survey VERB fbem-594 25 5 the the DET fbem-594 25 6 survey survey NOUN fbem-594 25 7 site site NOUN fbem-594 25 8 selected select VERB fbem-594 25 9 in in ADP fbem-594 25 10 this this DET fbem-594 25 11 subject subject NOUN fbem-594 25 12 is be AUX fbem-594 25 13 the the DET fbem-594 25 14 intersection intersection NOUN fbem-594 25 15 of of ADP fbem-594 25 16 yingbin yingbin PROPN fbem-594 25 17 road road NOUN fbem-594 25 18 and and CCONJ fbem-594 25 19 shiji shiji ADJ fbem-594 25 20 road road NOUN fbem-594 25 21 in in ADP fbem-594 25 22 jiaozuo jiaozuo PROPN fbem-594 25 23 , , PUNCT fbem-594 25 24 henan henan PROPN fbem-594 25 25 province province PROPN fbem-594 25 26 . . PUNCT fbem-594 26 1 the the DET fbem-594 26 2 road road NOUN fbem-594 26 3 plan plan NOUN fbem-594 26 4 of of ADP fbem-594 26 5 the the DET fbem-594 26 6 survey survey NOUN fbem-594 26 7 site site NOUN fbem-594 26 8 is be AUX fbem-594 26 9 shown show VERB fbem-594 26 10 in in ADP fbem-594 26 11 figure figure NOUN fbem-594 26 12 1 1 NUM fbem-594 26 13 . . PUNCT fbem-594 26 14 figure figure NOUN fbem-594 26 15 1 1 NUM fbem-594 26 16 . . PUNCT fbem-594 27 1 intersection intersection NOUN fbem-594 27 2 of of ADP fbem-594 27 3 ying ying PROPN fbem-594 27 4 bin bin PROPN fbem-594 27 5 road road NOUN fbem-594 27 6 and and CCONJ fbem-594 27 7 century century NOUN fbem-594 27 8 road road NOUN fbem-594 27 9 2.1 2.1 NUM fbem-594 27 10 . . PUNCT fbem-594 28 1 intersection intersection NOUN fbem-594 28 2 traffic traffic NOUN fbem-594 28 3 volume volume NOUN fbem-594 28 4 survey survey NOUN fbem-594 28 5 manually manually ADV fbem-594 28 6 count count VERB fbem-594 28 7 and and CCONJ fbem-594 28 8 observe observe VERB fbem-594 28 9 the the DET fbem-594 28 10 traffic traffic NOUN fbem-594 28 11 flow flow NOUN fbem-594 28 12 at at ADP fbem-594 28 13 the the DET fbem-594 28 14 intersection intersection NOUN fbem-594 28 15 . . PUNCT fbem-594 29 1 the the DET fbem-594 29 2 design design NOUN fbem-594 29 3 of of ADP fbem-594 29 4 the the DET fbem-594 29 5 questionnaire questionnaire NOUN fbem-594 29 6 is be AUX fbem-594 29 7 shown show VERB fbem-594 29 8 in in ADP fbem-594 29 9 figure figure NOUN fbem-594 29 10 2 2 NUM fbem-594 29 11 ( ( PUNCT fbem-594 29 12 taking take VERB fbem-594 29 13 the the DET fbem-594 29 14 east east ADJ fbem-594 29 15 entrance entrance NOUN fbem-594 29 16 as as ADP fbem-594 29 17 an an DET fbem-594 29 18 example example NOUN fbem-594 29 19 ) ) PUNCT fbem-594 29 20 . . PUNCT fbem-594 30 1 2 2 NUM fbem-594 30 2 figure figure NOUN fbem-594 30 3 2 2 NUM fbem-594 30 4 . . PUNCT fbem-594 30 5 manual manual ADJ fbem-594 30 6 counting counting NOUN fbem-594 30 7 questionnaire questionnaire NOUN fbem-594 30 8 design design NOUN fbem-594 30 9 table table NOUN fbem-594 30 10 the the DET fbem-594 30 11 flow flow NOUN fbem-594 30 12 in in ADP fbem-594 30 13 the the DET fbem-594 30 14 morning morning NOUN fbem-594 30 15 peak peak NOUN fbem-594 30 16 period period NOUN fbem-594 30 17 was be AUX fbem-594 30 18 investigated investigate VERB fbem-594 30 19 , , PUNCT fbem-594 30 20 and and CCONJ fbem-594 30 21 the the DET fbem-594 30 22 number number NOUN fbem-594 30 23 of of ADP fbem-594 30 24 motor motor NOUN fbem-594 30 25 vehicles vehicle NOUN fbem-594 30 26 and and CCONJ fbem-594 30 27 non non ADJ fbem-594 30 28 motor motor NOUN fbem-594 30 29 vehicles vehicle NOUN fbem-594 30 30 were be AUX fbem-594 30 31 counted count VERB fbem-594 30 32 at at ADP fbem-594 30 33 an an DET fbem-594 30 34 interval interval NOUN fbem-594 30 35 of of ADP fbem-594 30 36 15 15 NUM fbem-594 30 37 minutes minute NOUN fbem-594 30 38 . . PUNCT fbem-594 31 1 the the DET fbem-594 31 2 survey survey NOUN fbem-594 31 3 time time NOUN fbem-594 31 4 is be AUX fbem-594 31 5 one one NUM fbem-594 31 6 hour hour NOUN fbem-594 31 7 , , PUNCT fbem-594 31 8 from from ADP fbem-594 31 9 7:00 7:00 NUM fbem-594 31 10 to to ADP fbem-594 31 11 8:00 8:00 NUM fbem-594 31 12 . . PUNCT fbem-594 32 1 the the DET fbem-594 32 2 hourly hourly ADJ fbem-594 32 3 traffic traffic NOUN fbem-594 32 4 volume volume NOUN fbem-594 32 5 of of ADP fbem-594 32 6 each each DET fbem-594 32 7 lane lane NOUN fbem-594 32 8 and and CCONJ fbem-594 32 9 direction direction NOUN fbem-594 32 10 is be AUX fbem-594 32 11 obtained obtain VERB fbem-594 32 12 by by ADP fbem-594 32 13 summarizing summarize VERB fbem-594 32 14 the the DET fbem-594 32 15 survey survey NOUN fbem-594 32 16 data datum NOUN fbem-594 32 17 , , PUNCT fbem-594 32 18 as as SCONJ fbem-594 32 19 shown show VERB fbem-594 32 20 in in ADP fbem-594 32 21 table table NOUN fbem-594 32 22 1 1 NUM fbem-594 32 23 . . PUNCT fbem-594 32 24 table table NOUN fbem-594 32 25 1 1 NUM fbem-594 32 26 . . PUNCT fbem-594 33 1 hourly hourly ADJ fbem-594 33 2 traffic traffic NOUN fbem-594 33 3 volume volume NOUN fbem-594 33 4 in in ADP fbem-594 33 5 all all DET fbem-594 33 6 directions direction NOUN fbem-594 33 7 at at ADP fbem-594 33 8 the the DET fbem-594 33 9 intersection intersection NOUN fbem-594 33 10 of of ADP fbem-594 33 11 century century NOUN fbem-594 33 12 road road NOUN fbem-594 33 13 and and CCONJ fbem-594 33 14 yingbin yingbin PROPN fbem-594 33 15 road road NOUN fbem-594 33 16 30min 30min PROPN fbem-594 33 17 peak peak PROPN fbem-594 33 18 motor motor NOUN fbem-594 33 19 vehicle vehicle NOUN fbem-594 33 20 ( ( PUNCT fbem-594 33 21 pcu pcu PROPN fbem-594 33 22 / / SYM fbem-594 33 23 h h NOUN fbem-594 33 24 ) ) PUNCT fbem-594 33 25 east east NOUN fbem-594 33 26 import import NOUN fbem-594 33 27 turn turn NOUN fbem-594 33 28 lift lift VERB fbem-594 33 29 71 71 NUM fbem-594 33 30 straight straight ADJ fbem-594 33 31 312 312 NUM fbem-594 33 32 turn turn NOUN fbem-594 33 33 right right ADJ fbem-594 33 34 24 24 NUM fbem-594 33 35 west west ADJ fbem-594 33 36 import import NOUN fbem-594 33 37 turn turn NOUN fbem-594 33 38 lift lift VERB fbem-594 33 39 68 68 NUM fbem-594 33 40 straight straight ADJ fbem-594 33 41 306 306 NUM fbem-594 33 42 turn turn NOUN fbem-594 33 43 right right ADJ fbem-594 33 44 18 18 NUM fbem-594 33 45 south south ADJ fbem-594 33 46 import import NOUN fbem-594 33 47 turn turn NOUN fbem-594 33 48 lift lift VERB fbem-594 33 49 65 65 NUM fbem-594 33 50 straight straight ADJ fbem-594 33 51 320 320 NUM fbem-594 33 52 turn turn NOUN fbem-594 33 53 right right ADJ fbem-594 33 54 21 21 NUM fbem-594 33 55 north north NOUN fbem-594 33 56 import import NOUN fbem-594 33 57 turn turn NOUN fbem-594 33 58 lift lift VERB fbem-594 33 59 69 69 NUM fbem-594 33 60 straight straight ADJ fbem-594 33 61 298 298 NUM fbem-594 33 62 turn turn NOUN fbem-594 33 63 right right ADJ fbem-594 33 64 19 19 NUM fbem-594 33 65 total total ADJ fbem-594 33 66 1591 1591 NUM fbem-594 33 67 2.2 2.2 NUM fbem-594 33 68 . . PUNCT fbem-594 34 1 investigation investigation NOUN fbem-594 34 2 on on ADP fbem-594 34 3 the the DET fbem-594 34 4 current current ADJ fbem-594 34 5 situation situation NOUN fbem-594 34 6 of of ADP fbem-594 34 7 intersection intersection NOUN fbem-594 34 8 signal signal NOUN fbem-594 34 9 timing timing NOUN fbem-594 34 10 control control NOUN fbem-594 34 11 through through ADP fbem-594 34 12 observation observation NOUN fbem-594 34 13 , , PUNCT fbem-594 34 14 it it PRON fbem-594 34 15 can can AUX fbem-594 34 16 be be AUX fbem-594 34 17 seen see VERB fbem-594 34 18 that that SCONJ fbem-594 34 19 there there PRON fbem-594 34 20 are be VERB fbem-594 34 21 four four NUM fbem-594 34 22 phases phase NOUN fbem-594 34 23 in in ADP fbem-594 34 24 the the DET fbem-594 34 25 intersection intersection NOUN fbem-594 34 26 . . PUNCT fbem-594 35 1 the the DET fbem-594 35 2 first first ADJ fbem-594 35 3 phase phase NOUN fbem-594 35 4 is be AUX fbem-594 35 5 straight straight ADJ fbem-594 35 6 from from ADP fbem-594 35 7 north north NOUN fbem-594 35 8 to to ADP fbem-594 35 9 south south NOUN fbem-594 35 10 , , PUNCT fbem-594 35 11 turning turn VERB fbem-594 35 12 left leave VERB fbem-594 35 13 from from ADP fbem-594 35 14 north north NOUN fbem-594 35 15 to to ADP fbem-594 35 16 south south PROPN fbem-594 35 17 is be AUX fbem-594 35 18 the the DET fbem-594 35 19 second second ADJ fbem-594 35 20 phase phase NOUN fbem-594 35 21 , , PUNCT fbem-594 35 22 straight straight ADV fbem-594 35 23 from from ADP fbem-594 35 24 east east PROPN fbem-594 35 25 to to ADP fbem-594 35 26 west west PROPN fbem-594 35 27 is be AUX fbem-594 35 28 the the DET fbem-594 35 29 third third ADJ fbem-594 35 30 phase phase NOUN fbem-594 35 31 , , PUNCT fbem-594 35 32 and and CCONJ fbem-594 35 33 turning turn VERB fbem-594 35 34 left leave VERB fbem-594 35 35 from from ADP fbem-594 35 36 east east PROPN fbem-594 35 37 to to ADP fbem-594 35 38 west west PROPN fbem-594 35 39 is be AUX fbem-594 35 40 the the DET fbem-594 35 41 fourth fourth ADJ fbem-594 35 42 phase phase NOUN fbem-594 35 43 . . PUNCT fbem-594 36 1 the the DET fbem-594 36 2 schematic schematic ADJ fbem-594 36 3 diagram diagram NOUN fbem-594 36 4 is be AUX fbem-594 36 5 shown show VERB fbem-594 36 6 in in ADP fbem-594 36 7 figure figure NOUN fbem-594 36 8 3 3 NUM fbem-594 36 9 . . PUNCT fbem-594 36 10 by by ADP fbem-594 36 11 recording record VERB fbem-594 36 12 the the DET fbem-594 36 13 red red ADJ fbem-594 36 14 light light ADJ fbem-594 36 15 time time NOUN fbem-594 36 16 , , PUNCT fbem-594 36 17 yellow yellow ADJ fbem-594 36 18 light light ADJ fbem-594 36 19 time time NOUN fbem-594 36 20 and and CCONJ fbem-594 36 21 full full ADJ fbem-594 36 22 red red ADJ fbem-594 36 23 time time NOUN fbem-594 36 24 of of ADP fbem-594 36 25 each each DET fbem-594 36 26 phase phase NOUN fbem-594 36 27 , , PUNCT fbem-594 36 28 the the DET fbem-594 36 29 signal signal ADJ fbem-594 36 30 timing timing NOUN fbem-594 36 31 of of ADP fbem-594 36 32 each each DET fbem-594 36 33 phase phase NOUN fbem-594 36 34 of of ADP fbem-594 36 35 a a DET fbem-594 36 36 signal signal ADJ fbem-594 36 37 cycle cycle NOUN fbem-594 36 38 is be AUX fbem-594 36 39 obtained obtain VERB fbem-594 36 40 , , PUNCT fbem-594 36 41 as as SCONJ fbem-594 36 42 shown show VERB fbem-594 36 43 in in ADP fbem-594 36 44 figure figure NOUN fbem-594 36 45 4 4 NUM fbem-594 36 46 . . PUNCT fbem-594 36 47 figure figure VERB fbem-594 36 48 3 3 NUM fbem-594 36 49 . . PUNCT fbem-594 36 50 schematic schematic ADJ fbem-594 36 51 diagram diagram NOUN fbem-594 36 52 of of ADP fbem-594 36 53 signal signal ADJ fbem-594 36 54 phase phase NOUN fbem-594 36 55 at at ADP fbem-594 36 56 the the DET fbem-594 36 57 intersection intersection NOUN fbem-594 36 58 of of ADP fbem-594 36 59 yingbin yingbin PROPN fbem-594 36 60 road road NOUN fbem-594 36 61 and and CCONJ fbem-594 36 62 shiji shiji ADJ fbem-594 36 63 road road NOUN fbem-594 36 64 figure figure NOUN fbem-594 36 65 4 4 NUM fbem-594 36 66 . . PUNCT fbem-594 36 67 schematic schematic ADJ fbem-594 36 68 diagram diagram NOUN fbem-594 36 69 of of ADP fbem-594 36 70 signal signal ADJ fbem-594 36 71 timing timing NOUN fbem-594 36 72 at at ADP fbem-594 36 73 the the DET fbem-594 36 74 intersection intersection NOUN fbem-594 36 75 of of ADP fbem-594 36 76 ying ying PROPN fbem-594 36 77 bin bin PROPN fbem-594 36 78 road road PROPN fbem-594 36 79 and and CCONJ fbem-594 36 80 shi shi PROPN fbem-594 36 81 ji ji PROPN fbem-594 36 82 road road PROPN fbem-594 36 83 3 3 NUM fbem-594 36 84 3 3 NUM fbem-594 36 85 . . PUNCT fbem-594 37 1 traffic traffic NOUN fbem-594 37 2 flow flow NOUN fbem-594 37 3 simulation simulation NOUN fbem-594 37 4 3.1 3.1 NUM fbem-594 37 5 . . PUNCT fbem-594 37 6 simulation simulation NOUN fbem-594 37 7 road road NOUN fbem-594 37 8 network network NOUN fbem-594 37 9 drawing draw VERB fbem-594 37 10 after after ADP fbem-594 37 11 observing observe VERB fbem-594 37 12 the the DET fbem-594 37 13 actual actual ADJ fbem-594 37 14 road road NOUN fbem-594 37 15 situation situation NOUN fbem-594 37 16 at at ADP fbem-594 37 17 the the DET fbem-594 37 18 intersection intersection NOUN fbem-594 37 19 of of ADP fbem-594 37 20 shiji shiji PROPN fbem-594 37 21 road road NOUN fbem-594 37 22 and and CCONJ fbem-594 37 23 yingbin yingbin PROPN fbem-594 37 24 road road NOUN fbem-594 37 25 , , PUNCT fbem-594 37 26 it it PRON fbem-594 37 27 can can AUX fbem-594 37 28 be be AUX fbem-594 37 29 seen see VERB fbem-594 37 30 that that SCONJ fbem-594 37 31 there there PRON fbem-594 37 32 is be VERB fbem-594 37 33 one one NUM fbem-594 37 34 left leave VERB fbem-594 37 35 turn turn NOUN fbem-594 37 36 lane lane NOUN fbem-594 37 37 , , PUNCT fbem-594 37 38 two two NUM fbem-594 37 39 through through ADP fbem-594 37 40 lanes lane NOUN fbem-594 37 41 and and CCONJ fbem-594 37 42 one one NUM fbem-594 37 43 right right ADJ fbem-594 37 44 turn turn NOUN fbem-594 37 45 lane lane NOUN fbem-594 37 46 at at ADP fbem-594 37 47 the the DET fbem-594 37 48 south south ADJ fbem-594 37 49 entrance entrance NOUN fbem-594 37 50 , , PUNCT fbem-594 37 51 one one NUM fbem-594 37 52 left left AUX fbem-594 37 53 turn turn NOUN fbem-594 37 54 lane lane NOUN fbem-594 37 55 , , PUNCT fbem-594 37 56 two two NUM fbem-594 37 57 through through ADP fbem-594 37 58 lanes lane NOUN fbem-594 37 59 and and CCONJ fbem-594 37 60 one one NUM fbem-594 37 61 right right ADJ fbem-594 37 62 turn turn NOUN fbem-594 37 63 lane lane NOUN fbem-594 37 64 at at ADP fbem-594 37 65 the the DET fbem-594 37 66 north north NOUN fbem-594 37 67 entrance entrance NOUN fbem-594 37 68 , , PUNCT fbem-594 37 69 one one NUM fbem-594 37 70 left left AUX fbem-594 37 71 turn turn NOUN fbem-594 37 72 lane lane NOUN fbem-594 37 73 , , PUNCT fbem-594 37 74 two two NUM fbem-594 37 75 through through ADP fbem-594 37 76 lanes lane NOUN fbem-594 37 77 and and CCONJ fbem-594 37 78 one one NUM fbem-594 37 79 right right ADJ fbem-594 37 80 turn turn NOUN fbem-594 37 81 lane lane NOUN fbem-594 37 82 at at ADP fbem-594 37 83 the the DET fbem-594 37 84 east east NOUN fbem-594 37 85 entrance entrance NOUN fbem-594 37 86 , , PUNCT fbem-594 37 87 one one NUM fbem-594 37 88 left left AUX fbem-594 37 89 turn turn NOUN fbem-594 37 90 lane lane NOUN fbem-594 37 91 , , PUNCT fbem-594 37 92 two two NUM fbem-594 37 93 through through ADP fbem-594 37 94 lanes lane NOUN fbem-594 37 95 and and CCONJ fbem-594 37 96 one one NUM fbem-594 37 97 right right ADJ fbem-594 37 98 turn turn NOUN fbem-594 37 99 lane lane NOUN fbem-594 37 100 at at ADP fbem-594 37 101 the the DET fbem-594 37 102 west west NOUN fbem-594 37 103 entrance entrance NOUN fbem-594 37 104 , , PUNCT fbem-594 37 105 the the DET fbem-594 37 106 width width NOUN fbem-594 37 107 of of ADP fbem-594 37 108 each each DET fbem-594 37 109 lane lane NOUN fbem-594 37 110 is be AUX fbem-594 37 111 755 755 NUM fbem-594 37 112 m m NOUN fbem-594 37 113 , , PUNCT fbem-594 37 114 as as SCONJ fbem-594 37 115 shown show VERB fbem-594 37 116 in in ADP fbem-594 37 117 the the DET fbem-594 37 118 figure figure NOUN fbem-594 37 119 . . PUNCT fbem-594 38 1 the the DET fbem-594 38 2 width width NOUN fbem-594 38 3 of of ADP fbem-594 38 4 each each DET fbem-594 38 5 lane lane NOUN fbem-594 38 6 at at ADP fbem-594 38 7 the the DET fbem-594 38 8 entrance entrance NOUN fbem-594 38 9 and and CCONJ fbem-594 38 10 exit exit NOUN fbem-594 38 11 of of ADP fbem-594 38 12 each each DET fbem-594 38 13 lane lane NOUN fbem-594 38 14 is be AUX fbem-594 38 15 754.5 754.5 NUM fbem-594 38 16 m. m. NOUN fbem-594 38 17 3.2 3.2 NUM fbem-594 38 18 . . PUNCT fbem-594 39 1 signal signal NOUN fbem-594 39 2 timing timing NOUN fbem-594 39 3 and and CCONJ fbem-594 39 4 input input NOUN fbem-594 39 5 of of ADP fbem-594 39 6 hourly hourly ADJ fbem-594 39 7 traffic traffic NOUN fbem-594 39 8 volume volume NOUN fbem-594 39 9 it it PRON fbem-594 39 10 can can AUX fbem-594 39 11 be be AUX fbem-594 39 12 seen see VERB fbem-594 39 13 from from ADP fbem-594 39 14 2.1 2.1 NUM fbem-594 39 15 that that PRON fbem-594 39 16 the the DET fbem-594 39 17 hourly hourly ADJ fbem-594 39 18 traffic traffic NOUN fbem-594 39 19 flow flow NOUN fbem-594 39 20 in in ADP fbem-594 39 21 all all DET fbem-594 39 22 directions direction NOUN fbem-594 39 23 of of ADP fbem-594 39 24 each each DET fbem-594 39 25 entrance entrance NOUN fbem-594 39 26 lane lane NOUN fbem-594 39 27 at at ADP fbem-594 39 28 the the DET fbem-594 39 29 intersection intersection NOUN fbem-594 39 30 of of ADP fbem-594 39 31 ying ying PROPN fbem-594 39 32 bin bin PROPN fbem-594 39 33 road road PROPN fbem-594 39 34 and and CCONJ fbem-594 39 35 shi shi PROPN fbem-594 39 36 ji ji PROPN fbem-594 39 37 road road PROPN fbem-594 39 38 is be AUX fbem-594 39 39 shown show VERB fbem-594 39 40 in in ADP fbem-594 39 41 table table NOUN fbem-594 39 42 1 1 NUM fbem-594 39 43 , , PUNCT fbem-594 39 44 and and CCONJ fbem-594 39 45 the the DET fbem-594 39 46 input input NOUN fbem-594 39 47 vissim vissim PROPN fbem-594 39 48 simulation simulation PROPN fbem-594 39 49 model model NOUN fbem-594 39 50 is be AUX fbem-594 39 51 shown show VERB fbem-594 39 52 in in ADP fbem-594 39 53 figure figure NOUN fbem-594 39 54 6 6 NUM fbem-594 39 55 . . PUNCT fbem-594 39 56 figure figure NOUN fbem-594 39 57 5 5 NUM fbem-594 39 58 . . PUNCT fbem-594 40 1 schematic schematic ADJ fbem-594 40 2 diagram diagram NOUN fbem-594 40 3 of of ADP fbem-594 40 4 simulated simulate VERB fbem-594 40 5 intersection intersection NOUN fbem-594 40 6 of of ADP fbem-594 40 7 yingbin yingbin PROPN fbem-594 40 8 road road NOUN fbem-594 40 9 and and CCONJ fbem-594 40 10 shiji shiji ADJ fbem-594 40 11 road road NOUN fbem-594 40 12 figure figure NOUN fbem-594 40 13 6 6 NUM fbem-594 40 14 . . PUNCT fbem-594 41 1 hourly hourly ADJ fbem-594 41 2 traffic traffic NOUN fbem-594 41 3 input input NOUN fbem-594 41 4 simulation simulation NOUN fbem-594 41 5 model model NOUN fbem-594 41 6 figure figure NOUN fbem-594 41 7 7 7 NUM fbem-594 41 8 . . NOUN fbem-594 41 9 signal signal PROPN fbem-594 41 10 timing timing NOUN fbem-594 41 11 input input NOUN fbem-594 41 12 simulation simulation NOUN fbem-594 41 13 model model NOUN fbem-594 41 14 it it PRON fbem-594 41 15 can can AUX fbem-594 41 16 be be AUX fbem-594 41 17 seen see VERB fbem-594 41 18 from from ADP fbem-594 41 19 2.2 2.2 NUM fbem-594 41 20 that that SCONJ fbem-594 41 21 the the DET fbem-594 41 22 signal signal ADJ fbem-594 41 23 timing timing NOUN fbem-594 41 24 of of ADP fbem-594 41 25 each each DET fbem-594 41 26 phase phase NOUN fbem-594 41 27 at at ADP fbem-594 41 28 the the DET fbem-594 41 29 intersection intersection NOUN fbem-594 41 30 of of ADP fbem-594 41 31 ying ying PROPN fbem-594 41 32 bin bin PROPN fbem-594 41 33 road road PROPN fbem-594 41 34 and and CCONJ fbem-594 41 35 shi shi PROPN fbem-594 41 36 ji ji PROPN fbem-594 41 37 road road PROPN fbem-594 41 38 is be AUX fbem-594 41 39 shown show VERB fbem-594 41 40 in in ADP fbem-594 41 41 figure figure NOUN fbem-594 41 42 4 4 NUM fbem-594 41 43 , , PUNCT fbem-594 41 44 and and CCONJ fbem-594 41 45 the the DET fbem-594 41 46 input input NOUN fbem-594 41 47 vissim vissim PROPN fbem-594 41 48 simulation simulation PROPN fbem-594 41 49 model model NOUN fbem-594 41 50 is be AUX fbem-594 41 51 shown show VERB fbem-594 41 52 in in ADP fbem-594 41 53 figure figure NOUN fbem-594 41 54 7 7 NUM fbem-594 41 55 . . NOUN fbem-594 41 56 4 4 NUM fbem-594 41 57 3.3 3.3 NUM fbem-594 41 58 . . PUNCT fbem-594 42 1 output output NOUN fbem-594 42 2 of of ADP fbem-594 42 3 link link NOUN fbem-594 42 4 travel travel NOUN fbem-594 42 5 time time NOUN fbem-594 42 6 and and CCONJ fbem-594 42 7 number number NOUN fbem-594 42 8 of of ADP fbem-594 42 9 vehicles vehicle NOUN fbem-594 42 10 after after SCONJ fbem-594 42 11 the the DET fbem-594 42 12 simulation simulation NOUN fbem-594 42 13 road road NOUN fbem-594 42 14 network network NOUN fbem-594 42 15 is be AUX fbem-594 42 16 drawn draw VERB fbem-594 42 17 in in ADP fbem-594 42 18 chapters chapter NOUN fbem-594 42 19 3.1 3.1 NUM fbem-594 42 20 and and CCONJ fbem-594 42 21 3.2 3.2 NUM fbem-594 42 22 , , PUNCT fbem-594 42 23 and and CCONJ fbem-594 42 24 the the DET fbem-594 42 25 hourly hourly ADJ fbem-594 42 26 traffic traffic NOUN fbem-594 42 27 volume volume NOUN fbem-594 42 28 and and CCONJ fbem-594 42 29 signal signal VERB fbem-594 42 30 timing timing NOUN fbem-594 42 31 in in ADP fbem-594 42 32 all all DET fbem-594 42 33 directions direction NOUN fbem-594 42 34 of of ADP fbem-594 42 35 each each DET fbem-594 42 36 entrance entrance NOUN fbem-594 42 37 road road NOUN fbem-594 42 38 are be AUX fbem-594 42 39 input input VERB fbem-594 42 40 into into ADP fbem-594 42 41 the the DET fbem-594 42 42 simulation simulation NOUN fbem-594 42 43 model model NOUN fbem-594 42 44 , , PUNCT fbem-594 42 45 the the DET fbem-594 42 46 simulation simulation NOUN fbem-594 42 47 road road NOUN fbem-594 42 48 network network NOUN fbem-594 42 49 will will AUX fbem-594 42 50 be be AUX fbem-594 42 51 built build VERB fbem-594 42 52 successfully successfully ADV fbem-594 42 53 . . PUNCT fbem-594 43 1 click click VERB fbem-594 43 2 the the DET fbem-594 43 3 start start NOUN fbem-594 43 4 button button NOUN fbem-594 43 5 to to PART fbem-594 43 6 run run VERB fbem-594 43 7 the the DET fbem-594 43 8 intersection intersection NOUN fbem-594 43 9 simulation simulation NOUN fbem-594 43 10 , , PUNCT fbem-594 43 11 as as SCONJ fbem-594 43 12 shown show VERB fbem-594 43 13 in in ADP fbem-594 43 14 figure figure NOUN fbem-594 43 15 8 8 NUM fbem-594 43 16 . . PUNCT fbem-594 43 17 figure figure NOUN fbem-594 43 18 8 8 NUM fbem-594 43 19 . . PUNCT fbem-594 44 1 simulation simulation NOUN fbem-594 44 2 running run VERB fbem-594 44 3 effect effect NOUN fbem-594 44 4 after after ADP fbem-594 44 5 the the DET fbem-594 44 6 simulation simulation NOUN fbem-594 44 7 operation operation NOUN fbem-594 44 8 , , PUNCT fbem-594 44 9 one one NUM fbem-594 44 10 hour hour NOUN fbem-594 44 11 traffic traffic NOUN fbem-594 44 12 volume volume NOUN fbem-594 44 13 data datum NOUN fbem-594 44 14 of of ADP fbem-594 44 15 the the DET fbem-594 44 16 intersection intersection NOUN fbem-594 44 17 will will AUX fbem-594 44 18 be be AUX fbem-594 44 19 obtained obtain VERB fbem-594 44 20 , , PUNCT fbem-594 44 21 including include VERB fbem-594 44 22 road road NOUN fbem-594 44 23 network network NOUN fbem-594 44 24 data datum NOUN fbem-594 44 25 such such ADJ fbem-594 44 26 as as ADP fbem-594 44 27 travel travel NOUN fbem-594 44 28 time time NOUN fbem-594 44 29 , , PUNCT fbem-594 44 30 number number NOUN fbem-594 44 31 of of ADP fbem-594 44 32 vehicles vehicle NOUN fbem-594 44 33 passing pass VERB fbem-594 44 34 through through ADP fbem-594 44 35 the the DET fbem-594 44 36 road road NOUN fbem-594 44 37 section section NOUN fbem-594 44 38 , , PUNCT fbem-594 44 39 delay delay VERB fbem-594 44 40 time time NOUN fbem-594 44 41 and and CCONJ fbem-594 44 42 queue queue NOUN fbem-594 44 43 length length NOUN fbem-594 44 44 . . PUNCT fbem-594 45 1 since since SCONJ fbem-594 45 2 this this DET fbem-594 45 3 paper paper NOUN fbem-594 45 4 predicts predict VERB fbem-594 45 5 the the DET fbem-594 45 6 traffic traffic NOUN fbem-594 45 7 flow flow NOUN fbem-594 45 8 direction direction NOUN fbem-594 45 9 of of ADP fbem-594 45 10 the the DET fbem-594 45 11 intersection intersection NOUN fbem-594 45 12 based base VERB fbem-594 45 13 on on ADP fbem-594 45 14 the the DET fbem-594 45 15 travel travel NOUN fbem-594 45 16 time time NOUN fbem-594 45 17 of of ADP fbem-594 45 18 the the DET fbem-594 45 19 road road NOUN fbem-594 45 20 section section NOUN fbem-594 45 21 and and CCONJ fbem-594 45 22 the the DET fbem-594 45 23 number number NOUN fbem-594 45 24 of of ADP fbem-594 45 25 vehicles vehicle NOUN fbem-594 45 26 passing pass VERB fbem-594 45 27 through through ADP fbem-594 45 28 the the DET fbem-594 45 29 road road NOUN fbem-594 45 30 section section NOUN fbem-594 45 31 combined combine VERB fbem-594 45 32 with with ADP fbem-594 45 33 knn knn PROPN fbem-594 45 34 algorithm algorithm PROPN fbem-594 45 35 , , PUNCT fbem-594 45 36 this this DET fbem-594 45 37 paper paper NOUN fbem-594 45 38 outputs output VERB fbem-594 45 39 the the DET fbem-594 45 40 road road NOUN fbem-594 45 41 network network NOUN fbem-594 45 42 data datum NOUN fbem-594 45 43 in in ADP fbem-594 45 44 a a DET fbem-594 45 45 time time NOUN fbem-594 45 46 period period NOUN fbem-594 45 47 of of ADP fbem-594 45 48 5min 5min NOUN fbem-594 45 49 , , PUNCT fbem-594 45 50 the the DET fbem-594 45 51 travel travel NOUN fbem-594 45 52 time time NOUN fbem-594 45 53 of of ADP fbem-594 45 54 the the DET fbem-594 45 55 output output NOUN fbem-594 45 56 section section NOUN fbem-594 45 57 and and CCONJ fbem-594 45 58 the the DET fbem-594 45 59 number number NOUN fbem-594 45 60 of of ADP fbem-594 45 61 vehicles vehicle NOUN fbem-594 45 62 passing pass VERB fbem-594 45 63 through through ADP fbem-594 45 64 the the DET fbem-594 45 65 section section NOUN fbem-594 45 66 are be AUX fbem-594 45 67 shown show VERB fbem-594 45 68 in in ADP fbem-594 45 69 figure figure NOUN fbem-594 45 70 9 9 NUM fbem-594 45 71 ( ( PUNCT fbem-594 45 72 only only ADV fbem-594 45 73 some some DET fbem-594 45 74 data datum NOUN fbem-594 45 75 are be AUX fbem-594 45 76 intercepted intercept VERB fbem-594 45 77 ) ) PUNCT fbem-594 45 78 . . PUNCT fbem-594 46 1 figure figure NOUN fbem-594 46 2 9 9 NUM fbem-594 46 3 . . PUNCT fbem-594 47 1 simulation simulation NOUN fbem-594 47 2 output output PROPN fbem-594 47 3 data datum NOUN fbem-594 47 4 taking take VERB fbem-594 47 5 300s 300 NOUN fbem-594 47 6 as as ADP fbem-594 47 7 a a DET fbem-594 47 8 time time NOUN fbem-594 47 9 period period NOUN fbem-594 47 10 , , PUNCT fbem-594 47 11 the the DET fbem-594 47 12 data datum NOUN fbem-594 47 13 obtained obtain VERB fbem-594 47 14 are be AUX fbem-594 47 15 as as SCONJ fbem-594 47 16 shown show VERB fbem-594 47 17 in in ADP fbem-594 47 18 figure figure NOUN fbem-594 47 19 9 9 NUM fbem-594 47 20 . . PUNCT fbem-594 48 1 each each DET fbem-594 48 2 line line NOUN fbem-594 48 3 includes include VERB fbem-594 48 4 the the DET fbem-594 48 5 section section NOUN fbem-594 48 6 number number NOUN fbem-594 48 7 , , PUNCT fbem-594 48 8 the the DET fbem-594 48 9 travel travel NOUN fbem-594 48 10 time time NOUN fbem-594 48 11 of of ADP fbem-594 48 12 this this DET fbem-594 48 13 time time NOUN fbem-594 48 14 period period NOUN fbem-594 48 15 and and CCONJ fbem-594 48 16 the the DET fbem-594 48 17 number number NOUN fbem-594 48 18 of of ADP fbem-594 48 19 vehicles vehicle NOUN fbem-594 48 20 passing pass VERB fbem-594 48 21 through through ADP fbem-594 48 22 this this DET fbem-594 48 23 section section NOUN fbem-594 48 24 in in ADP fbem-594 48 25 this this DET fbem-594 48 26 time time NOUN fbem-594 48 27 period period NOUN fbem-594 48 28 . . PUNCT fbem-594 49 1 section section NOUN fbem-594 49 2 numbers number NOUN fbem-594 49 3 1 1 NUM fbem-594 49 4 , , PUNCT fbem-594 49 5 2 2 NUM fbem-594 49 6 , , PUNCT fbem-594 49 7 ... ... PUNCT fbem-594 49 8 , , PUNCT fbem-594 49 9 12 12 NUM fbem-594 49 10 successively successively ADV fbem-594 49 11 represent represent VERB fbem-594 49 12 west west PROPN fbem-594 49 13 east east PROPN fbem-594 49 14 straight straight ADJ fbem-594 49 15 line line NOUN fbem-594 49 16 , , PUNCT fbem-594 49 17 west west PROPN fbem-594 49 18 east east PROPN fbem-594 49 19 right right ADJ fbem-594 49 20 turn turn NOUN fbem-594 49 21 , , PUNCT fbem-594 49 22 west west PROPN fbem-594 49 23 east east PROPN fbem-594 49 24 left leave VERB fbem-594 49 25 turn turn NOUN fbem-594 49 26 , , PUNCT fbem-594 49 27 north north NOUN fbem-594 49 28 south south ADJ fbem-594 49 29 5 5 NUM fbem-594 49 30 straight straight ADJ fbem-594 49 31 line line NOUN fbem-594 49 32 , , PUNCT fbem-594 49 33 north north NOUN fbem-594 49 34 south south ADJ fbem-594 49 35 right right ADJ fbem-594 49 36 turn turn NOUN fbem-594 49 37 , , PUNCT fbem-594 49 38 north north PROPN fbem-594 49 39 south south PROPN fbem-594 49 40 left leave VERB fbem-594 49 41 turn turn NOUN fbem-594 49 42 , , PUNCT fbem-594 49 43 east east PROPN fbem-594 49 44 west west PROPN fbem-594 49 45 straight straight ADJ fbem-594 49 46 line line NOUN fbem-594 49 47 , , PUNCT fbem-594 49 48 east east PROPN fbem-594 49 49 west west PROPN fbem-594 49 50 right right ADJ fbem-594 49 51 turn turn NOUN fbem-594 49 52 , , PUNCT fbem-594 49 53 east east PROPN fbem-594 49 54 west west PROPN fbem-594 49 55 left leave VERB fbem-594 49 56 turn turn NOUN fbem-594 49 57 , , PUNCT fbem-594 49 58 north north NOUN fbem-594 49 59 south south ADJ fbem-594 49 60 straight straight ADJ fbem-594 49 61 line line NOUN fbem-594 49 62 , , PUNCT fbem-594 49 63 north north PROPN fbem-594 49 64 south south PROPN fbem-594 49 65 left leave VERB fbem-594 49 66 turn turn NOUN fbem-594 49 67 , , PUNCT fbem-594 49 68 north north NOUN fbem-594 49 69 south south ADV fbem-594 49 70 right right ADJ fbem-594 49 71 turn turn NOUN fbem-594 49 72 , , PUNCT fbem-594 49 73 take take VERB fbem-594 49 74 the the DET fbem-594 49 75 west west PROPN fbem-594 49 76 east east PROPN fbem-594 49 77 direct direct ADJ fbem-594 49 78 behavior behavior NOUN fbem-594 49 79 as as ADP fbem-594 49 80 an an DET fbem-594 49 81 example example NOUN fbem-594 49 82 , , PUNCT fbem-594 49 83 which which PRON fbem-594 49 84 means mean VERB fbem-594 49 85 from from ADP fbem-594 49 86 west west PROPN fbem-594 49 87 import import PROPN fbem-594 49 88 to to ADP fbem-594 49 89 east east NOUN fbem-594 49 90 export export NOUN fbem-594 49 91 . . PUNCT fbem-594 50 1 4 4 X fbem-594 50 2 . . X fbem-594 50 3 build build VERB fbem-594 50 4 model model NOUN fbem-594 50 5 4.1 4.1 NUM fbem-594 50 6 . . PUNCT fbem-594 51 1 k k PROPN fbem-594 51 2 nearest near ADJ fbem-594 51 3 neighbor neighbor PROPN fbem-594 51 4 algorithm algorithm PROPN fbem-594 51 5 the the DET fbem-594 51 6 basic basic ADJ fbem-594 51 7 idea idea NOUN fbem-594 51 8 of of ADP fbem-594 51 9 k k PROPN fbem-594 51 10 nearest near ADJ fbem-594 51 11 neighbor neighbor NOUN fbem-594 51 12 ( ( PUNCT fbem-594 51 13 knn knn PROPN fbem-594 51 14 ) ) PUNCT fbem-594 51 15 algorithm algorithm NOUN fbem-594 51 16 is be AUX fbem-594 51 17 to to PART fbem-594 51 18 match match VERB fbem-594 51 19 the the DET fbem-594 51 20 current current ADJ fbem-594 51 21 input input NOUN fbem-594 51 22 variable variable NOUN fbem-594 51 23 with with ADP fbem-594 51 24 the the DET fbem-594 51 25 historical historical ADJ fbem-594 51 26 data data NOUN fbem-594 51 27 value value NOUN fbem-594 51 28 with with ADP fbem-594 51 29 similar similar ADJ fbem-594 51 30 input input NOUN fbem-594 51 31 variables variable NOUN fbem-594 51 32 , , PUNCT fbem-594 51 33 in in ADP fbem-594 51 34 which which PRON fbem-594 51 35 the the DET fbem-594 51 36 input input NOUN fbem-594 51 37 variables variable NOUN fbem-594 51 38 are be AUX fbem-594 51 39 usually usually ADV fbem-594 51 40 called call VERB fbem-594 51 41 eigenvectors eigenvector NOUN fbem-594 51 42 . . PUNCT fbem-594 52 1 each each DET fbem-594 52 2 feature feature NOUN fbem-594 52 3 vector vector NOUN fbem-594 52 4 describes describe VERB fbem-594 52 5 a a DET fbem-594 52 6 point point NOUN fbem-594 52 7 in in ADP fbem-594 52 8 the the DET fbem-594 52 9 multivariable multivariable ADJ fbem-594 52 10 space space NOUN fbem-594 52 11 called call VERB fbem-594 52 12 feature feature NOUN fbem-594 52 13 space space NOUN fbem-594 52 14 . . PUNCT fbem-594 53 1 if if SCONJ fbem-594 53 2 the the DET fbem-594 53 3 feature feature NOUN fbem-594 53 4 vector vector NOUN fbem-594 53 5 contains contain VERB fbem-594 53 6 n n PRON fbem-594 53 7 attribute attribute NOUN fbem-594 53 8 values value NOUN fbem-594 53 9 , , PUNCT fbem-594 53 10 the the DET fbem-594 53 11 feature feature NOUN fbem-594 53 12 space space NOUN fbem-594 53 13 is be AUX fbem-594 53 14 n n ADV fbem-594 53 15 - - PUNCT fbem-594 53 16 dimensional dimensional ADJ fbem-594 53 17 . . PUNCT fbem-594 54 1 the the DET fbem-594 54 2 output output NOUN fbem-594 54 3 value value NOUN fbem-594 54 4 of of ADP fbem-594 54 5 knn knn PROPN fbem-594 54 6 algorithm algorithm PROPN fbem-594 54 7 is be AUX fbem-594 54 8 defined define VERB fbem-594 54 9 as as ADP fbem-594 54 10 a a DET fbem-594 54 11 function function NOUN fbem-594 54 12 related relate VERB fbem-594 54 13 to to ADP fbem-594 54 14 the the DET fbem-594 54 15 known know VERB fbem-594 54 16 output output NOUN fbem-594 54 17 history history NOUN fbem-594 54 18 of of ADP fbem-594 54 19 input input NOUN fbem-594 54 20 eigenvectors eigenvector NOUN fbem-594 54 21 with with ADP fbem-594 54 22 similar similar ADJ fbem-594 54 23 eigenvectors eigenvector NOUN fbem-594 54 24 . . PUNCT fbem-594 55 1 π‘Œπ‘‘ π‘Œπ‘‘ PROPN fbem-594 55 2 is be AUX fbem-594 55 3 the the DET fbem-594 55 4 predicted predict VERB fbem-594 55 5 value value NOUN fbem-594 55 6 of of ADP fbem-594 55 7 the the DET fbem-594 55 8 set set ADJ fbem-594 55 9 period period NOUN fbem-594 55 10 of of ADP fbem-594 55 11 t t PROPN fbem-594 55 12 , , PUNCT fbem-594 55 13 which which PRON fbem-594 55 14 is be AUX fbem-594 55 15 represented represent VERB fbem-594 55 16 by by ADP fbem-594 55 17 a a DET fbem-594 55 18 predicted predict VERB fbem-594 55 19 value value NOUN fbem-594 55 20 of of ADP fbem-594 55 21 the the DET fbem-594 55 22 set set ADJ fbem-594 55 23 period period NOUN fbem-594 55 24 of of ADP fbem-594 55 25 t. t. PROPN fbem-594 55 26 in in ADP fbem-594 55 27 knn knn PROPN fbem-594 55 28 algorithm algorithm PROPN fbem-594 55 29 , , PUNCT fbem-594 55 30 for for ADP fbem-594 55 31 a a DET fbem-594 55 32 given give VERB fbem-594 55 33 input input NOUN fbem-594 55 34 eigenvector eigenvector NOUN fbem-594 55 35 𝑋𝑑 𝑋𝑑 PROPN fbem-594 55 36 , , PUNCT fbem-594 55 37 k k PROPN fbem-594 55 38 historical historical ADJ fbem-594 55 39 eigenvectors eigenvector NOUN fbem-594 55 40 π‘‹β„Ž1 π‘‹β„Ž1 VERB fbem-594 55 41 , , PUNCT fbem-594 55 42 π‘‹β„Ž2 π‘‹β„Ž2 NOUN fbem-594 55 43 , , PUNCT fbem-594 55 44 … … PUNCT fbem-594 55 45 , , PUNCT fbem-594 55 46 π‘‹β„Žπ‘˜ π‘‹β„Žπ‘˜ PROPN fbem-594 55 47 , , PUNCT fbem-594 55 48 closest close ADJ fbem-594 55 49 to to ADP fbem-594 55 50 the the DET fbem-594 55 51 input input NOUN fbem-594 55 52 eigenvector eigenvector NOUN fbem-594 55 53 π‘Œπ‘‘ π‘Œπ‘‘ PROPN fbem-594 55 54 are be AUX fbem-594 55 55 searched search VERB fbem-594 55 56 in in ADP fbem-594 55 57 the the DET fbem-594 55 58 historical historical ADJ fbem-594 55 59 data datum NOUN fbem-594 55 60 set set VERB fbem-594 55 61 , , PUNCT fbem-594 55 62 and and CCONJ fbem-594 55 63 then then ADV fbem-594 55 64 the the DET fbem-594 55 65 k k PROPN fbem-594 55 66 eigenvectors eigenvector NOUN fbem-594 55 67 are be AUX fbem-594 55 68 solved solve VERB fbem-594 55 69 by by ADP fbem-594 55 70 weighted weighted ADJ fbem-594 55 71 estimation estimation NOUN fbem-594 55 72 . . PUNCT fbem-594 56 1 4.2 4.2 NUM fbem-594 56 2 . . X fbem-594 56 3 construct construct VERB fbem-594 56 4 feature feature NOUN fbem-594 56 5 vector vector NOUN fbem-594 56 6 the the DET fbem-594 56 7 composition composition NOUN fbem-594 56 8 of of ADP fbem-594 56 9 the the DET fbem-594 56 10 feature feature NOUN fbem-594 56 11 vector vector NOUN fbem-594 56 12 needs need VERB fbem-594 56 13 to to PART fbem-594 56 14 have have VERB fbem-594 56 15 a a DET fbem-594 56 16 certain certain ADJ fbem-594 56 17 correlation correlation NOUN fbem-594 56 18 with with ADP fbem-594 56 19 the the DET fbem-594 56 20 travel travel NOUN fbem-594 56 21 time time NOUN fbem-594 56 22 of of ADP fbem-594 56 23 the the DET fbem-594 56 24 road road NOUN fbem-594 56 25 section section NOUN fbem-594 56 26 , , PUNCT fbem-594 56 27 and and CCONJ fbem-594 56 28 can can AUX fbem-594 56 29 reflect reflect VERB fbem-594 56 30 the the DET fbem-594 56 31 differences difference NOUN fbem-594 56 32 of of ADP fbem-594 56 33 the the DET fbem-594 56 34 same same ADJ fbem-594 56 35 road road NOUN fbem-594 56 36 section section NOUN fbem-594 56 37 at at ADP fbem-594 56 38 different different ADJ fbem-594 56 39 times time NOUN fbem-594 56 40 . . PUNCT fbem-594 57 1 in in ADP fbem-594 57 2 order order NOUN fbem-594 57 3 to to PART fbem-594 57 4 meet meet VERB fbem-594 57 5 the the DET fbem-594 57 6 needs need NOUN fbem-594 57 7 of of ADP fbem-594 57 8 real real ADJ fbem-594 57 9 - - PUNCT fbem-594 57 10 time time NOUN fbem-594 57 11 prediction prediction NOUN fbem-594 57 12 , , PUNCT fbem-594 57 13 the the DET fbem-594 57 14 feature feature NOUN fbem-594 57 15 vector vector NOUN fbem-594 57 16 also also ADV fbem-594 57 17 needs need VERB fbem-594 57 18 to to PART fbem-594 57 19 be be AUX fbem-594 57 20 easily easily ADV fbem-594 57 21 calculated calculate VERB fbem-594 57 22 from from ADP fbem-594 57 23 the the DET fbem-594 57 24 historical historical ADJ fbem-594 57 25 data datum NOUN fbem-594 57 26 set set VERB fbem-594 57 27 . . PUNCT fbem-594 58 1 due due ADP fbem-594 58 2 to to ADP fbem-594 58 3 the the DET fbem-594 58 4 characteristics characteristic NOUN fbem-594 58 5 of of ADP fbem-594 58 6 traffic traffic NOUN fbem-594 58 7 flow flow NOUN fbem-594 58 8 , , PUNCT fbem-594 58 9 the the DET fbem-594 58 10 travel travel NOUN fbem-594 58 11 time time NOUN fbem-594 58 12 has have VERB fbem-594 58 13 a a DET fbem-594 58 14 certain certain ADJ fbem-594 58 15 autocorrelation autocorrelation NOUN fbem-594 58 16 in in ADP fbem-594 58 17 the the DET fbem-594 58 18 time time NOUN fbem-594 58 19 series series NOUN fbem-594 58 20 . . PUNCT fbem-594 59 1 generally generally ADV fbem-594 59 2 , , PUNCT fbem-594 59 3 the the DET fbem-594 59 4 travel travel NOUN fbem-594 59 5 time time NOUN fbem-594 59 6 of of ADP fbem-594 59 7 the the DET fbem-594 59 8 first first ADJ fbem-594 59 9 few few ADJ fbem-594 59 10 time time NOUN fbem-594 59 11 periods period NOUN fbem-594 59 12 of of ADP fbem-594 59 13 the the DET fbem-594 59 14 current current ADJ fbem-594 59 15 time time NOUN fbem-594 59 16 period period NOUN fbem-594 59 17 is be AUX fbem-594 59 18 selected select VERB fbem-594 59 19 as as ADP fbem-594 59 20 a a DET fbem-594 59 21 part part NOUN fbem-594 59 22 of of ADP fbem-594 59 23 the the DET fbem-594 59 24 feature feature NOUN fbem-594 59 25 vector vector NOUN fbem-594 59 26 . . PUNCT fbem-594 60 1 due due ADP fbem-594 60 2 to to ADP fbem-594 60 3 data datum NOUN fbem-594 60 4 limitations limitation NOUN fbem-594 60 5 , , PUNCT fbem-594 60 6 only only ADV fbem-594 60 7 the the DET fbem-594 60 8 travel travel NOUN fbem-594 60 9 time time NOUN fbem-594 60 10 of of ADP fbem-594 60 11 the the DET fbem-594 60 12 current current ADJ fbem-594 60 13 time time NOUN fbem-594 60 14 period period NOUN fbem-594 60 15 is be AUX fbem-594 60 16 selected select VERB fbem-594 60 17 as as ADP fbem-594 60 18 a a DET fbem-594 60 19 part part NOUN fbem-594 60 20 of of ADP fbem-594 60 21 the the DET fbem-594 60 22 feature feature NOUN fbem-594 60 23 vector vector NOUN fbem-594 60 24 . . PUNCT fbem-594 61 1 the the DET fbem-594 61 2 number number NOUN fbem-594 61 3 of of ADP fbem-594 61 4 vehicles vehicle NOUN fbem-594 61 5 passing pass VERB fbem-594 61 6 through through ADP fbem-594 61 7 this this DET fbem-594 61 8 section section NOUN fbem-594 61 9 in in ADP fbem-594 61 10 a a DET fbem-594 61 11 period period NOUN fbem-594 61 12 of of ADP fbem-594 61 13 time time NOUN fbem-594 61 14 also also ADV fbem-594 61 15 reflects reflect VERB fbem-594 61 16 the the DET fbem-594 61 17 traffic traffic NOUN fbem-594 61 18 situation situation NOUN fbem-594 61 19 of of ADP fbem-594 61 20 the the DET fbem-594 61 21 current current ADJ fbem-594 61 22 road road NOUN fbem-594 61 23 , , PUNCT fbem-594 61 24 which which PRON fbem-594 61 25 is be AUX fbem-594 61 26 greatly greatly ADV fbem-594 61 27 related relate VERB fbem-594 61 28 to to ADP fbem-594 61 29 the the DET fbem-594 61 30 travel travel NOUN fbem-594 61 31 time time NOUN fbem-594 61 32 of of ADP fbem-594 61 33 the the DET fbem-594 61 34 current current ADJ fbem-594 61 35 road road NOUN fbem-594 61 36 . . PUNCT fbem-594 62 1 for for ADP fbem-594 62 2 two two NUM fbem-594 62 3 acquisition acquisition NOUN fbem-594 62 4 points point NOUN fbem-594 62 5 a a PRON fbem-594 62 6 and and CCONJ fbem-594 62 7 b b NOUN fbem-594 62 8 at at ADP fbem-594 62 9 both both DET fbem-594 62 10 ends end NOUN fbem-594 62 11 of of ADP fbem-594 62 12 a a DET fbem-594 62 13 road road NOUN fbem-594 62 14 , , PUNCT fbem-594 62 15 the the DET fbem-594 62 16 number number NOUN fbem-594 62 17 of of ADP fbem-594 62 18 vehicles vehicle NOUN fbem-594 62 19 passing pass VERB fbem-594 62 20 through through ADP fbem-594 62 21 acquisition acquisition NOUN fbem-594 62 22 points point NOUN fbem-594 62 23 a a PRON fbem-594 62 24 and and CCONJ fbem-594 62 25 b b NOUN fbem-594 62 26 in in ADP fbem-594 62 27 time time NOUN fbem-594 62 28 period period NOUN fbem-594 62 29 p p NOUN fbem-594 62 30 is be AUX fbem-594 62 31 taken take VERB fbem-594 62 32 as as ADP fbem-594 62 33 a a DET fbem-594 62 34 part part NOUN fbem-594 62 35 of of ADP fbem-594 62 36 the the DET fbem-594 62 37 feature feature NOUN fbem-594 62 38 vector vector NOUN fbem-594 62 39 in in ADP fbem-594 62 40 time time NOUN fbem-594 62 41 period period NOUN fbem-594 62 42 p p NOUN fbem-594 62 43 , , PUNCT fbem-594 62 44 and and CCONJ fbem-594 62 45 the the DET fbem-594 62 46 expression expression NOUN fbem-594 62 47 of of ADP fbem-594 62 48 the the DET fbem-594 62 49 feature feature NOUN fbem-594 62 50 vector vector NOUN fbem-594 62 51 in in ADP fbem-594 62 52 time time NOUN fbem-594 62 53 period period NOUN fbem-594 62 54 p p X fbem-594 62 55 : : PUNCT fbem-594 62 56 [ [ X fbem-594 62 57 t t X fbem-594 62 58 , , PUNCT fbem-594 62 59 n n CCONJ fbem-594 62 60 ] ] PUNCT fbem-594 62 61 4.3 4.3 NUM fbem-594 62 62 . . PUNCT fbem-594 63 1 k k PROPN fbem-594 63 2 value value NOUN fbem-594 63 3 determination determination NOUN fbem-594 63 4 k k PROPN fbem-594 63 5 value value NOUN fbem-594 63 6 is be AUX fbem-594 63 7 the the DET fbem-594 63 8 only only ADJ fbem-594 63 9 parameter parameter NOUN fbem-594 63 10 in in ADP fbem-594 63 11 knn knn PROPN fbem-594 63 12 algorithm algorithm PROPN fbem-594 63 13 , , PUNCT fbem-594 63 14 and and CCONJ fbem-594 63 15 its its PRON fbem-594 63 16 selection selection NOUN fbem-594 63 17 is be AUX fbem-594 63 18 directly directly ADV fbem-594 63 19 related relate VERB fbem-594 63 20 to to ADP fbem-594 63 21 the the DET fbem-594 63 22 accuracy accuracy NOUN fbem-594 63 23 of of ADP fbem-594 63 24 prediction prediction NOUN fbem-594 63 25 results result NOUN fbem-594 63 26 . . PUNCT fbem-594 64 1 this this DET fbem-594 64 2 paper paper NOUN fbem-594 64 3 uses use VERB fbem-594 64 4 cross cross VERB fbem-594 64 5 validation validation NOUN fbem-594 64 6 to to PART fbem-594 64 7 determine determine VERB fbem-594 64 8 the the DET fbem-594 64 9 optimal optimal ADJ fbem-594 64 10 k k PROPN fbem-594 64 11 value value NOUN fbem-594 64 12 . . PUNCT fbem-594 65 1 the the DET fbem-594 65 2 specific specific ADJ fbem-594 65 3 steps step NOUN fbem-594 65 4 are be AUX fbem-594 65 5 as as SCONJ fbem-594 65 6 follows follow VERB fbem-594 65 7 : : PUNCT fbem-594 65 8 ( ( PUNCT fbem-594 65 9 1 1 NUM fbem-594 65 10 ): ): PUNCT fbem-594 65 11 the the DET fbem-594 65 12 minimum minimum ADJ fbem-594 65 13 and and CCONJ fbem-594 65 14 maximum maximum ADJ fbem-594 65 15 values value NOUN fbem-594 65 16 of of ADP fbem-594 65 17 πΎπ‘šπ‘–π‘› πΎπ‘šπ‘–π‘› PROPN fbem-594 65 18 and and CCONJ fbem-594 65 19 πΎπ‘šπ‘Žπ‘₯ πΎπ‘šπ‘Žπ‘₯ PROPN fbem-594 65 20 are be AUX fbem-594 65 21 selected select VERB fbem-594 65 22 respectively respectively ADV fbem-594 65 23 . . PUNCT fbem-594 66 1 ( ( PUNCT fbem-594 66 2 2):divide 2):divide NUM fbem-594 66 3 the the DET fbem-594 66 4 road road NOUN fbem-594 66 5 section section NOUN fbem-594 66 6 r r NOUN fbem-594 66 7 data datum NOUN fbem-594 66 8 set set VERB fbem-594 66 9 into into ADP fbem-594 66 10 m m PROPN fbem-594 66 11 parts part NOUN fbem-594 66 12 at at ADP fbem-594 66 13 random random ADJ fbem-594 66 14 to to PART fbem-594 66 15 obtain obtain VERB fbem-594 66 16 the the DET fbem-594 66 17 data datum NOUN fbem-594 66 18 set set VERB fbem-594 66 19 𝐷1，𝐷2， 𝐷1，𝐷2， NOUN fbem-594 66 20 … … SYM fbem-594 66 21 οΌŒπ·π‘€ οΌŒπ·π‘€ PROPN fbem-594 66 22 , , PUNCT fbem-594 66 23 and and CCONJ fbem-594 66 24 then then ADV fbem-594 66 25 successively successively ADV fbem-594 66 26 take take VERB fbem-594 66 27 the the DET fbem-594 66 28 data datum NOUN fbem-594 66 29 set set VERB fbem-594 67 1 𝐷𝑖 𝐷𝑖 PROPN fbem-594 67 2 ( ( PUNCT fbem-594 67 3 i i NOUN fbem-594 67 4 = = NOUN fbem-594 67 5 1 1 NUM fbem-594 67 6 , , PUNCT fbem-594 67 7 2 2 NUM fbem-594 67 8 , , PUNCT fbem-594 67 9 ... ... PUNCT fbem-594 67 10 , , PUNCT fbem-594 67 11 m m VERB fbem-594 67 12 ) ) PUNCT fbem-594 67 13 as as SCONJ fbem-594 67 14 the the DET fbem-594 67 15 test test NOUN fbem-594 67 16 data datum NOUN fbem-594 67 17 set set VERB fbem-594 67 18 and and CCONJ fbem-594 67 19 the the DET fbem-594 67 20 other other ADJ fbem-594 67 21 m-1 m-1 PROPN fbem-594 67 22 data datum NOUN fbem-594 67 23 sets set NOUN fbem-594 67 24 as as ADP fbem-594 67 25 the the DET fbem-594 67 26 historical historical ADJ fbem-594 67 27 data datum NOUN fbem-594 67 28 set set VERB fbem-594 67 29 . . PUNCT fbem-594 68 1 ( ( PUNCT fbem-594 68 2 3 3 X fbem-594 68 3 ) ) PUNCT fbem-594 68 4 taking take VERB fbem-594 68 5 𝐾 𝐾 PROPN fbem-594 68 6 = = PUNCT fbem-594 68 7 𝐾0 𝐾0 PROPN fbem-594 68 8 , , PUNCT fbem-594 68 9 𝐾0 𝐾0 PROPN fbem-594 68 10 is be AUX fbem-594 68 11 between between ADP fbem-594 68 12 πΎπ‘šπ‘–π‘› πΎπ‘šπ‘–π‘› PROPN fbem-594 68 13 and and CCONJ fbem-594 68 14 πΎπ‘šπ‘Žπ‘₯ πΎπ‘šπ‘Žπ‘₯ PROPN fbem-594 68 15 . . PUNCT fbem-594 69 1 calculate calculate VERB fbem-594 69 2 the the DET fbem-594 69 3 average average ADJ fbem-594 69 4 absolute absolute ADJ fbem-594 69 5 error error NOUN fbem-594 69 6 percentage percentage NOUN fbem-594 69 7 of of ADP fbem-594 69 8 the the DET fbem-594 69 9 test test NOUN fbem-594 69 10 data datum NOUN fbem-594 69 11 set set VERB fbem-594 69 12 𝐷𝑖. 𝐷𝑖. PROPN fbem-594 69 13 𝐸 𝐸 PROPN fbem-594 69 14 𝐾0,𝑀𝑖 𝐾0,𝑀𝑖 ADP fbem-594 69 15 100 100 NUM fbem-594 69 16 % % NOUN fbem-594 69 17 𝑁𝑝 𝑁𝑝 NOUN fbem-594 69 18 βˆ‘ βˆ‘ NOUN fbem-594 69 19 π‘Ÿ π‘Ÿ PRON fbem-594 69 20 1 1 NUM fbem-594 69 21 𝑁𝑝 𝑁𝑝 NOUN fbem-594 69 22 β€Š β€Š SPACE fbem-594 69 23 π΄π‘Ÿ π΄π‘Ÿ PROPN fbem-594 69 24 𝐴𝑝 𝐴𝑝 PROPN fbem-594 69 25 π΄π‘Ÿ π΄π‘Ÿ PROPN fbem-594 69 26 ( ( PUNCT fbem-594 69 27 1 1 NUM fbem-594 69 28 ) ) PUNCT fbem-594 69 29 where where SCONJ fbem-594 69 30 : : PUNCT fbem-594 69 31 𝑁𝑝 𝑁𝑝 NOUN fbem-594 69 32 is be AUX fbem-594 69 33 the the DET fbem-594 69 34 sample sample NOUN fbem-594 69 35 size size NOUN fbem-594 69 36 in in ADP fbem-594 69 37 the the DET fbem-594 69 38 test test NOUN fbem-594 69 39 data datum NOUN fbem-594 69 40 set set VERB fbem-594 69 41 𝐷𝑖 𝐷𝑖 PROPN fbem-594 69 42 ; ; PUNCT fbem-594 69 43 π΄π‘Ÿ π΄π‘Ÿ PROPN fbem-594 69 44 is be AUX fbem-594 69 45 the the DET fbem-594 69 46 true true ADJ fbem-594 69 47 value value NOUN fbem-594 69 48 of of ADP fbem-594 69 49 record record NOUN fbem-594 69 50 r r NOUN fbem-594 69 51 in in ADP fbem-594 69 52 the the DET fbem-594 69 53 test test NOUN fbem-594 69 54 data datum NOUN fbem-594 69 55 set set VERB fbem-594 69 56 ; ; PUNCT fbem-594 69 57 when when SCONJ fbem-594 69 58 k k PROPN fbem-594 69 59 takes take VERB fbem-594 69 60 𝐾0 𝐾0 PROPN fbem-594 69 61 , , PUNCT fbem-594 69 62 𝐴𝑝 𝐴𝑝 PROPN fbem-594 69 63 is be AUX fbem-594 69 64 𝐾0 𝐾0 PROPN fbem-594 69 65 . . PUNCT fbem-594 70 1 the the DET fbem-594 70 2 predicted predict VERB fbem-594 70 3 value value NOUN fbem-594 70 4 obtained obtain VERB fbem-594 70 5 by by ADP fbem-594 70 6 applying apply VERB fbem-594 70 7 the the DET fbem-594 70 8 prediction prediction NOUN fbem-594 70 9 method method NOUN fbem-594 70 10 in in ADP fbem-594 70 11 the the DET fbem-594 70 12 test test NOUN fbem-594 70 13 data datum NOUN fbem-594 70 14 set set VERB fbem-594 70 15 𝐷𝑖. 𝐷𝑖. PROPN fbem-594 70 16 ( ( PUNCT fbem-594 70 17 4 4 NUM fbem-594 70 18 ) ) PUNCT fbem-594 70 19 when when SCONJ fbem-594 70 20 k k PROPN fbem-594 70 21 takes take VERB fbem-594 70 22 𝐾0 𝐾0 PROPN fbem-594 70 23 , , PUNCT fbem-594 70 24 calculate calculate VERB fbem-594 70 25 the the DET fbem-594 70 26 average average ADJ fbem-594 70 27 absolute absolute ADJ fbem-594 70 28 error error NOUN fbem-594 70 29 percentage percentage NOUN fbem-594 70 30 corresponding correspond VERB fbem-594 70 31 to to ADP fbem-594 70 32 m m PROPN fbem-594 70 33 data data NOUN fbem-594 70 34 sets set NOUN fbem-594 70 35 according accord VERB fbem-594 70 36 to to ADP fbem-594 70 37 the the DET fbem-594 70 38 above above ADJ fbem-594 70 39 formula formula NOUN fbem-594 70 40 , , PUNCT fbem-594 70 41 and and CCONJ fbem-594 70 42 calculate calculate VERB fbem-594 70 43 the the DET fbem-594 70 44 mean mean ADJ fbem-594 70 45 value value NOUN fbem-594 70 46 of of ADP fbem-594 70 47 these these DET fbem-594 70 48 m m NOUN fbem-594 70 49 values value NOUN fbem-594 70 50 : : PUNCT fbem-594 70 51 𝐸‾ 𝐸‾ VERB fbem-594 70 52 βˆ‘ βˆ‘ DET fbem-594 70 53 β€Š β€Š SPACE fbem-594 70 54 𝐸 𝐸 PROPN fbem-594 70 55 , , PUNCT fbem-594 70 56 ( ( PUNCT fbem-594 70 57 2 2 NUM fbem-594 70 58 ) ) PUNCT fbem-594 70 59 ( ( PUNCT fbem-594 70 60 5 5 NUM fbem-594 70 61 ) ) PUNCT fbem-594 70 62 when when SCONJ fbem-594 70 63 𝐸‾ 𝐸‾ PROPN fbem-594 70 64 takes take VERB fbem-594 70 65 the the DET fbem-594 70 66 minimum minimum ADJ fbem-594 70 67 value value NOUN fbem-594 70 68 , , PUNCT fbem-594 70 69 the the DET fbem-594 70 70 corresponding correspond VERB fbem-594 70 71 𝐾 𝐾 PROPN fbem-594 70 72 value value NOUN fbem-594 70 73 is be AUX fbem-594 70 74 the the DET fbem-594 70 75 optimal optimal ADJ fbem-594 70 76 𝐾. 𝐾. PROPN fbem-594 70 77 4.4 4.4 NUM fbem-594 70 78 . . PUNCT fbem-594 71 1 distance distance NOUN fbem-594 71 2 measurement measurement NOUN fbem-594 71 3 because because SCONJ fbem-594 71 4 the the DET fbem-594 71 5 feature feature NOUN fbem-594 71 6 vector vector NOUN fbem-594 71 7 includes include VERB fbem-594 71 8 two two NUM fbem-594 71 9 parts part NOUN fbem-594 71 10 , , PUNCT fbem-594 71 11 travel travel NOUN fbem-594 71 12 time time NOUN fbem-594 71 13 and and CCONJ fbem-594 71 14 the the DET fbem-594 71 15 number number NOUN fbem-594 71 16 of of ADP fbem-594 71 17 vehicles vehicle NOUN fbem-594 71 18 , , PUNCT fbem-594 71 19 the the DET fbem-594 71 20 distance distance NOUN fbem-594 71 21 between between ADP fbem-594 71 22 feature feature NOUN fbem-594 71 23 vectors vector NOUN fbem-594 71 24 is be AUX fbem-594 71 25 calculated calculate VERB fbem-594 71 26 by by ADP fbem-594 71 27 euclidean euclidean ADJ fbem-594 71 28 distance distance NOUN fbem-594 71 29 formula formula NOUN fbem-594 71 30 . . PUNCT fbem-594 72 1 𝑑 𝑑 VERB fbem-594 72 2 π‘₯ π‘₯ X fbem-594 72 3 π‘₯ π‘₯ X fbem-594 72 4 π‘₯ π‘₯ X fbem-594 72 5 π‘₯ π‘₯ X fbem-594 72 6 ( ( PUNCT fbem-594 72 7 3 3 NUM fbem-594 72 8 ) ) PUNCT fbem-594 72 9 4.5 4.5 NUM fbem-594 72 10 . . PUNCT fbem-594 73 1 traffic traffic NOUN fbem-594 73 2 flow flow NOUN fbem-594 73 3 direction direction NOUN fbem-594 73 4 prediction prediction NOUN fbem-594 73 5 firstly firstly ADV fbem-594 73 6 , , PUNCT fbem-594 73 7 the the DET fbem-594 73 8 k k PROPN fbem-594 73 9 feature feature NOUN fbem-594 73 10 vectors vector NOUN fbem-594 73 11 closest close ADJ fbem-594 73 12 to to ADP fbem-594 73 13 the the DET fbem-594 73 14 feature feature NOUN fbem-594 73 15 vectors vector NOUN fbem-594 73 16 of of ADP fbem-594 73 17 the the DET fbem-594 73 18 predicted predict VERB fbem-594 73 19 value value NOUN fbem-594 73 20 are be AUX fbem-594 73 21 found find VERB fbem-594 73 22 in in ADP fbem-594 73 23 the the DET fbem-594 73 24 historical historical ADJ fbem-594 73 25 data datum NOUN fbem-594 73 26 , , PUNCT fbem-594 73 27 and and CCONJ fbem-594 73 28 then then ADV fbem-594 73 29 the the DET fbem-594 73 30 value value NOUN fbem-594 73 31 corresponding correspond VERB fbem-594 73 32 to to ADP fbem-594 73 33 the the DET fbem-594 73 34 feature feature NOUN fbem-594 73 35 vector vector NOUN fbem-594 73 36 is be AUX fbem-594 73 37 weighted weight VERB fbem-594 73 38 and and CCONJ fbem-594 73 39 estimated estimate VERB fbem-594 73 40 to to PART fbem-594 73 41 obtain obtain VERB fbem-594 73 42 the the DET fbem-594 73 43 predicted predict VERB fbem-594 73 44 value value NOUN fbem-594 73 45 . . PUNCT fbem-594 74 1 since since SCONJ fbem-594 74 2 the the DET fbem-594 74 3 travel travel NOUN fbem-594 74 4 time time NOUN fbem-594 74 5 of of ADP fbem-594 74 6 the the DET fbem-594 74 7 historical historical ADJ fbem-594 74 8 data datum NOUN fbem-594 74 9 has have VERB fbem-594 74 10 a a DET fbem-594 74 11 greater great ADJ fbem-594 74 12 impact impact NOUN fbem-594 74 13 on on ADP fbem-594 74 14 the the DET fbem-594 74 15 predicted predict VERB fbem-594 74 16 value value NOUN fbem-594 74 17 when when SCONJ fbem-594 74 18 the the DET fbem-594 74 19 eigenvector eigenvector NOUN fbem-594 74 20 of of ADP fbem-594 74 21 the the DET fbem-594 74 22 historical historical ADJ fbem-594 74 23 data datum NOUN fbem-594 74 24 is be AUX fbem-594 74 25 closer close ADJ fbem-594 74 26 to to ADP fbem-594 74 27 the the DET fbem-594 74 28 eigenvector eigenvector NOUN fbem-594 74 29 of of ADP fbem-594 74 30 the the DET fbem-594 74 31 value value NOUN fbem-594 74 32 to to PART fbem-594 74 33 be be AUX fbem-594 74 34 predicted predict VERB fbem-594 74 35 , , PUNCT fbem-594 74 36 the the DET fbem-594 74 37 section section NOUN fbem-594 74 38 number number NOUN fbem-594 74 39 is be AUX fbem-594 74 40 obtained obtain VERB fbem-594 74 41 by by ADP fbem-594 74 42 weighting weight VERB fbem-594 74 43 . . PUNCT fbem-594 75 1 𝑇 𝑇 PROPN fbem-594 75 2 βˆ‘ βˆ‘ PUNCT fbem-594 75 3 β€Š β€Š SPACE fbem-594 75 4 πœ” πœ” PRON fbem-594 75 5 𝑋 𝑋 NOUN fbem-594 75 6 , , PUNCT fbem-594 75 7 𝑋 𝑋 PROPN fbem-594 75 8 𝑇 𝑇 PROPN fbem-594 75 9 ( ( PUNCT fbem-594 75 10 4 4 NUM fbem-594 75 11 ) ) PUNCT fbem-594 75 12 where where SCONJ fbem-594 75 13 : : PUNCT fbem-594 75 14 𝑇𝐾 𝑇𝐾 PROPN fbem-594 75 15 𝑝 𝑝 PROPN fbem-594 75 16 is be AUX fbem-594 75 17 the the DET fbem-594 75 18 number number NOUN fbem-594 75 19 of of ADP fbem-594 75 20 road road NOUN fbem-594 75 21 sections section NOUN fbem-594 75 22 to to PART fbem-594 75 23 be be AUX fbem-594 75 24 predicted predict VERB fbem-594 75 25 . . PUNCT fbem-594 76 1 𝑇𝐾 𝑇𝐾 NOUN fbem-594 76 2 𝑒 𝑒 NOUN fbem-594 76 3 is be AUX fbem-594 76 4 the the DET fbem-594 76 5 link link NOUN fbem-594 76 6 travel travel NOUN fbem-594 76 7 time time NOUN fbem-594 76 8 value value NOUN fbem-594 76 9 corresponding correspond VERB fbem-594 76 10 to to ADP fbem-594 76 11 the the DET fbem-594 76 12 feature feature NOUN fbem-594 76 13 vector vector NOUN fbem-594 76 14 𝑋𝑒 𝑋𝑒 PROPN fbem-594 76 15 ( ( PUNCT fbem-594 76 16 u u NOUN fbem-594 76 17 = = PROPN fbem-594 76 18 1 1 NUM fbem-594 76 19 , , PUNCT fbem-594 76 20 2 2 NUM fbem-594 76 21 , , PUNCT fbem-594 76 22 ... ... PUNCT fbem-594 76 23 , , PUNCT fbem-594 76 24 k k X fbem-594 76 25 ) ) PUNCT fbem-594 76 26 among among ADP fbem-594 76 27 the the DET fbem-594 76 28 k k PROPN fbem-594 76 29 adjacent adjacent ADJ fbem-594 76 30 historical historical ADJ fbem-594 76 31 feature feature NOUN fbem-594 76 32 vectors vector NOUN fbem-594 76 33 . . PUNCT fbem-594 77 1 πœ” πœ” ADP fbem-594 77 2 𝑋 𝑋 NOUN fbem-594 77 3 , , PUNCT fbem-594 77 4 𝑋 𝑋 PROPN fbem-594 77 5 is be AUX fbem-594 77 6 the the DET fbem-594 77 7 function function NOUN fbem-594 77 8 used use VERB fbem-594 77 9 for for ADP fbem-594 77 10 weighted weighted ADJ fbem-594 77 11 estimation estimation NOUN fbem-594 77 12 , , PUNCT fbem-594 77 13 πœ” πœ” ADP fbem-594 77 14 𝑋 𝑋 NOUN fbem-594 77 15 , , PUNCT fbem-594 77 16 𝑋 𝑋 NOUN fbem-594 77 17 , , PUNCT fbem-594 77 18 βˆ‘ βˆ‘ ADP fbem-594 77 19 β€Š β€Š SPACE fbem-594 77 20 , , PUNCT fbem-594 77 21 ( ( PUNCT fbem-594 77 22 5 5 NUM fbem-594 77 23 ) ) PUNCT fbem-594 77 24 where where SCONJ fbem-594 77 25 : : PUNCT fbem-594 77 26 𝑋𝑃 𝑋𝑃 PROPN fbem-594 77 27 𝑝 𝑝 PROPN fbem-594 77 28 is be AUX fbem-594 77 29 the the DET fbem-594 77 30 eigenvector eigenvector NOUN fbem-594 77 31 corresponding corresponding NOUN fbem-594 77 32 to to ADP fbem-594 77 33 section section NOUN fbem-594 77 34 r r NOUN fbem-594 77 35 in in ADP fbem-594 77 36 time time NOUN fbem-594 77 37 period period NOUN fbem-594 77 38 p p X fbem-594 77 39 ; ; PUNCT fbem-594 77 40 𝑋𝐻 𝑋𝐻 PROPN fbem-594 77 41 πœ” πœ” NOUN fbem-594 77 42 represents represent VERB fbem-594 77 43 one one NUM fbem-594 77 44 of of ADP fbem-594 77 45 the the DET fbem-594 77 46 k k PROPN fbem-594 77 47 nearest near ADJ fbem-594 77 48 historical historical ADJ fbem-594 77 49 eigenvectors eigenvector NOUN fbem-594 77 50 ; ; PUNCT fbem-594 77 51 𝑑 𝑑 PROPN fbem-594 77 52 𝑋 𝑋 PROPN fbem-594 77 53 , , PUNCT fbem-594 77 54 𝑋 𝑋 PROPN fbem-594 77 55 represents represent VERB fbem-594 77 56 the the DET fbem-594 77 57 distance distance NOUN fbem-594 77 58 between between ADP fbem-594 77 59 𝑋𝑃 𝑋𝑃 PROPN fbem-594 77 60 𝑝 𝑝 PROPN fbem-594 77 61 and and CCONJ fbem-594 77 62 vector vector NOUN fbem-594 77 63 𝑋𝐻 𝑋𝐻 PROPN fbem-594 77 64 𝑒 𝑒 NOUN fbem-594 77 65 obtained obtain VERB fbem-594 77 66 by by ADP fbem-594 77 67 the the DET fbem-594 77 68 eigenvector eigenvector NOUN fbem-594 77 69 similarity similarity PROPN fbem-594 77 70 measurement measurement NOUN fbem-594 77 71 method method NOUN fbem-594 77 72 . . PUNCT fbem-594 78 1 5 5 X fbem-594 78 2 . . X fbem-594 78 3 prediction prediction NOUN fbem-594 78 4 of of ADP fbem-594 78 5 traffic traffic NOUN fbem-594 78 6 flow flow NOUN fbem-594 78 7 direction direction NOUN fbem-594 78 8 based base VERB fbem-594 78 9 on on ADP fbem-594 78 10 k k NOUN fbem-594 78 11 - - PUNCT fbem-594 78 12 nearest near ADJ fbem-594 78 13 neighbor neighbor NOUN fbem-594 78 14 algorithm algorithm NOUN fbem-594 78 15 5.1 5.1 NUM fbem-594 78 16 . . PUNCT fbem-594 79 1 k k NOUN fbem-594 79 2 value value NOUN fbem-594 79 3 determination determination NOUN fbem-594 79 4 in in ADP fbem-594 79 5 knn knn PROPN fbem-594 79 6 algorithm algorithm PROPN fbem-594 79 7 , , PUNCT fbem-594 79 8 because because SCONJ fbem-594 79 9 the the DET fbem-594 79 10 selection selection NOUN fbem-594 79 11 of of ADP fbem-594 79 12 k k PROPN fbem-594 79 13 value value NOUN fbem-594 79 14 has have VERB fbem-594 79 15 a a DET fbem-594 79 16 great great ADJ fbem-594 79 17 impact impact NOUN fbem-594 79 18 on on ADP fbem-594 79 19 the the DET fbem-594 79 20 experimental experimental ADJ fbem-594 79 21 results result NOUN fbem-594 79 22 , , PUNCT fbem-594 79 23 the the DET fbem-594 79 24 optimal optimal ADJ fbem-594 79 25 k k PROPN fbem-594 79 26 selection selection NOUN fbem-594 79 27 is be AUX fbem-594 79 28 different different ADJ fbem-594 79 29 in in ADP fbem-594 79 30 different different ADJ fbem-594 79 31 sections section NOUN fbem-594 79 32 and and CCONJ fbem-594 79 33 at at ADP fbem-594 79 34 different different ADJ fbem-594 79 35 times time NOUN fbem-594 79 36 . . PUNCT fbem-594 80 1 therefore therefore ADV fbem-594 80 2 , , PUNCT fbem-594 80 3 this this DET fbem-594 80 4 section section NOUN fbem-594 80 5 first first ADV fbem-594 80 6 carries carry VERB fbem-594 80 7 out out ADP fbem-594 80 8 relevant relevant ADJ fbem-594 80 9 experiments experiment NOUN fbem-594 80 10 on on ADP fbem-594 80 11 the the DET fbem-594 80 12 calibration calibration NOUN fbem-594 80 13 of of ADP fbem-594 80 14 k k PROPN fbem-594 80 15 value value NOUN fbem-594 80 16 . . PUNCT fbem-594 81 1 the the DET fbem-594 81 2 k k PROPN fbem-594 81 3 value value NOUN fbem-594 81 4 is be AUX fbem-594 81 5 6 6 NUM fbem-594 81 6 selected select VERB fbem-594 81 7 from from ADP fbem-594 81 8 0 0 NUM fbem-594 81 9 to to ADP fbem-594 81 10 21 21 NUM fbem-594 81 11 , , PUNCT fbem-594 81 12 and and CCONJ fbem-594 81 13 the the DET fbem-594 81 14 average average ADJ fbem-594 81 15 relative relative ADJ fbem-594 81 16 error error NOUN fbem-594 81 17 of of ADP fbem-594 81 18 the the DET fbem-594 81 19 experimental experimental ADJ fbem-594 81 20 results result NOUN fbem-594 81 21 is be AUX fbem-594 81 22 calculated calculate VERB fbem-594 81 23 . . PUNCT fbem-594 82 1 the the DET fbem-594 82 2 results result NOUN fbem-594 82 3 are be AUX fbem-594 82 4 shown show VERB fbem-594 82 5 in in ADP fbem-594 82 6 figure figure NOUN fbem-594 82 7 10 10 NUM fbem-594 82 8 . . PUNCT fbem-594 83 1 figure figure NOUN fbem-594 83 2 10 10 NUM fbem-594 83 3 . . PUNCT fbem-594 84 1 the the DET fbem-594 84 2 average average ADJ fbem-594 84 3 relative relative ADJ fbem-594 84 4 error error NOUN fbem-594 84 5 varies vary VERB fbem-594 84 6 with with ADP fbem-594 84 7 the the DET fbem-594 84 8 value value NOUN fbem-594 84 9 of of ADP fbem-594 84 10 k k PROPN fbem-594 84 11 taking take VERB fbem-594 84 12 the the DET fbem-594 84 13 average average ADJ fbem-594 84 14 relative relative ADJ fbem-594 84 15 error error NOUN fbem-594 84 16 as as ADP fbem-594 84 17 the the DET fbem-594 84 18 y y NOUN fbem-594 84 19 - - PUNCT fbem-594 84 20 axis axis NOUN fbem-594 84 21 and and CCONJ fbem-594 84 22 the the DET fbem-594 84 23 kvalue kvalue NOUN fbem-594 84 24 as as ADP fbem-594 84 25 the the DET fbem-594 84 26 x x NOUN fbem-594 84 27 - - NOUN fbem-594 84 28 axis axis ADJ fbem-594 84 29 , , PUNCT fbem-594 84 30 it it PRON fbem-594 84 31 is be AUX fbem-594 84 32 displayed display VERB fbem-594 84 33 on on ADP fbem-594 84 34 the the DET fbem-594 84 35 image image NOUN fbem-594 84 36 , , PUNCT fbem-594 84 37 as as SCONJ fbem-594 84 38 shown show VERB fbem-594 84 39 in in ADP fbem-594 84 40 the the DET fbem-594 84 41 figure figure NOUN fbem-594 84 42 . . PUNCT fbem-594 85 1 it it PRON fbem-594 85 2 can can AUX fbem-594 85 3 be be AUX fbem-594 85 4 seen see VERB fbem-594 85 5 that that SCONJ fbem-594 85 6 when when SCONJ fbem-594 85 7 k k PROPN fbem-594 85 8 = = SYM fbem-594 85 9 18 18 NUM fbem-594 85 10 , , PUNCT fbem-594 85 11 the the DET fbem-594 85 12 value value NOUN fbem-594 85 13 of of ADP fbem-594 85 14 the the DET fbem-594 85 15 average average ADJ fbem-594 85 16 relative relative ADJ fbem-594 85 17 error error NOUN fbem-594 85 18 converges converge NOUN fbem-594 85 19 and and CCONJ fbem-594 85 20 tends tend VERB fbem-594 85 21 to to PART fbem-594 85 22 be be AUX fbem-594 85 23 stable stable ADJ fbem-594 85 24 , , PUNCT fbem-594 85 25 and and CCONJ fbem-594 85 26 the the DET fbem-594 85 27 average average ADJ fbem-594 85 28 relative relative ADJ fbem-594 85 29 error error NOUN fbem-594 85 30 tends tend VERB fbem-594 85 31 to to ADP fbem-594 85 32 0.27 0.27 NUM fbem-594 85 33 . . PUNCT fbem-594 86 1 therefore therefore ADV fbem-594 86 2 , , PUNCT fbem-594 86 3 k k PROPN fbem-594 86 4 is be AUX fbem-594 86 5 taken take VERB fbem-594 86 6 as as ADP fbem-594 86 7 18 18 NUM fbem-594 86 8 . . PUNCT fbem-594 87 1 5.2 5.2 NUM fbem-594 87 2 . . PUNCT fbem-594 88 1 traffic traffic NOUN fbem-594 88 2 flow flow NOUN fbem-594 88 3 direction direction NOUN fbem-594 88 4 prediction prediction NOUN fbem-594 88 5 due due ADP fbem-594 88 6 to to ADP fbem-594 88 7 the the DET fbem-594 88 8 small small ADJ fbem-594 88 9 amount amount NOUN fbem-594 88 10 of of ADP fbem-594 88 11 data datum NOUN fbem-594 88 12 , , PUNCT fbem-594 88 13 90 90 NUM fbem-594 88 14 % % NOUN fbem-594 88 15 of of ADP fbem-594 88 16 the the DET fbem-594 88 17 data datum NOUN fbem-594 88 18 is be AUX fbem-594 88 19 used use VERB fbem-594 88 20 for for ADP fbem-594 88 21 training training NOUN fbem-594 88 22 , , PUNCT fbem-594 88 23 and and CCONJ fbem-594 88 24 10 10 NUM fbem-594 88 25 % % NOUN fbem-594 88 26 of of ADP fbem-594 88 27 the the DET fbem-594 88 28 data datum NOUN fbem-594 88 29 is be AUX fbem-594 88 30 used use VERB fbem-594 88 31 to to PART fbem-594 88 32 test test VERB fbem-594 88 33 the the DET fbem-594 88 34 correctness correctness NOUN fbem-594 88 35 of of ADP fbem-594 88 36 the the DET fbem-594 88 37 predicted predict VERB fbem-594 88 38 traffic traffic NOUN fbem-594 88 39 flow flow NOUN fbem-594 88 40 direction direction NOUN fbem-594 88 41 . . PUNCT fbem-594 89 1 after after ADP fbem-594 89 2 allocation allocation NOUN fbem-594 89 3 , , PUNCT fbem-594 89 4 there there PRON fbem-594 89 5 are be VERB fbem-594 89 6 14 14 NUM fbem-594 89 7 groups group NOUN fbem-594 89 8 of of ADP fbem-594 89 9 test test NOUN fbem-594 89 10 data datum NOUN fbem-594 89 11 . . PUNCT fbem-594 90 1 after after ADP fbem-594 90 2 training training NOUN fbem-594 90 3 , , PUNCT fbem-594 90 4 input input VERB fbem-594 90 5 the the DET fbem-594 90 6 feature feature NOUN fbem-594 90 7 vectors vector NOUN fbem-594 90 8 of of ADP fbem-594 90 9 the the DET fbem-594 90 10 test test NOUN fbem-594 90 11 data datum NOUN fbem-594 90 12 into into ADP fbem-594 90 13 the the DET fbem-594 90 14 prediction prediction NOUN fbem-594 90 15 model model NOUN fbem-594 90 16 , , PUNCT fbem-594 90 17 and and CCONJ fbem-594 90 18 output output VERB fbem-594 90 19 the the DET fbem-594 90 20 predicted predict VERB fbem-594 90 21 traffic traffic NOUN fbem-594 90 22 flow flow NOUN fbem-594 90 23 number number NOUN fbem-594 90 24 of of ADP fbem-594 90 25 the the DET fbem-594 90 26 feature feature NOUN fbem-594 90 27 vectors vector NOUN fbem-594 90 28 of of ADP fbem-594 90 29 the the DET fbem-594 90 30 test test NOUN fbem-594 90 31 data datum NOUN fbem-594 90 32 , , PUNCT fbem-594 90 33 as as SCONJ fbem-594 90 34 shown show VERB fbem-594 90 35 in in ADP fbem-594 90 36 figure figure NOUN fbem-594 90 37 11 11 NUM fbem-594 90 38 . . PUNCT fbem-594 91 1 figure figure VERB fbem-594 91 2 11 11 NUM fbem-594 91 3 . . PUNCT fbem-594 92 1 traffic traffic NOUN fbem-594 92 2 flow flow NOUN fbem-594 92 3 direction direction NOUN fbem-594 92 4 can can AUX fbem-594 92 5 be be AUX fbem-594 92 6 predicted predict VERB fbem-594 92 7 the the DET fbem-594 92 8 predicted predict VERB fbem-594 92 9 traffic traffic NOUN fbem-594 92 10 flow flow NOUN fbem-594 92 11 number number NOUN fbem-594 92 12 and and CCONJ fbem-594 92 13 the the DET fbem-594 92 14 actual actual ADJ fbem-594 92 15 traffic traffic NOUN fbem-594 92 16 flow flow NOUN fbem-594 92 17 number number NOUN fbem-594 92 18 are be AUX fbem-594 92 19 displayed display VERB fbem-594 92 20 on on ADP fbem-594 92 21 the the DET fbem-594 92 22 image image NOUN fbem-594 92 23 , , PUNCT fbem-594 92 24 as as SCONJ fbem-594 92 25 shown show VERB fbem-594 92 26 in in ADP fbem-594 92 27 figure figure NOUN fbem-594 92 28 11 11 NUM fbem-594 92 29 . . PUNCT fbem-594 93 1 the the DET fbem-594 93 2 x x X fbem-594 93 3 - - NOUN fbem-594 93 4 axis axis NOUN fbem-594 93 5 represents represent VERB fbem-594 93 6 the the DET fbem-594 93 7 group group NOUN fbem-594 93 8 and and CCONJ fbem-594 93 9 the the DET fbem-594 93 10 y y NOUN fbem-594 93 11 - - PUNCT fbem-594 93 12 axis axis NOUN fbem-594 93 13 represents represent VERB fbem-594 93 14 the the DET fbem-594 93 15 traffic traffic NOUN fbem-594 93 16 flow flow NOUN fbem-594 93 17 direction direction NOUN fbem-594 93 18 number number NOUN fbem-594 93 19 , , PUNCT fbem-594 93 20 in in ADP fbem-594 93 21 which which PRON fbem-594 93 22 blue blue NOUN fbem-594 93 23 represents represent VERB fbem-594 93 24 the the DET fbem-594 93 25 actual actual ADJ fbem-594 93 26 traffic traffic NOUN fbem-594 93 27 flow flow NOUN fbem-594 93 28 direction direction NOUN fbem-594 93 29 and and CCONJ fbem-594 93 30 yellow yellow NOUN fbem-594 93 31 represents represent VERB fbem-594 93 32 the the DET fbem-594 93 33 predicted predict VERB fbem-594 93 34 traffic traffic NOUN fbem-594 93 35 flow flow NOUN fbem-594 93 36 direction direction NOUN fbem-594 93 37 . . PUNCT fbem-594 94 1 when when SCONJ fbem-594 94 2 the the DET fbem-594 94 3 predicted predict VERB fbem-594 94 4 traffic traffic NOUN fbem-594 94 5 flow flow NOUN fbem-594 94 6 direction direction NOUN fbem-594 94 7 is be AUX fbem-594 94 8 the the DET fbem-594 94 9 same same ADJ fbem-594 94 10 as as ADP fbem-594 94 11 the the DET fbem-594 94 12 actual actual ADJ fbem-594 94 13 traffic traffic NOUN fbem-594 94 14 flow flow NOUN fbem-594 94 15 direction direction NOUN fbem-594 94 16 , , PUNCT fbem-594 94 17 it it PRON fbem-594 94 18 is be AUX fbem-594 94 19 displayed display VERB fbem-594 94 20 in in ADP fbem-594 94 21 red red PROPN fbem-594 94 22 . . PUNCT fbem-594 95 1 it it PRON fbem-594 95 2 can can AUX fbem-594 95 3 be be AUX fbem-594 95 4 seen see VERB fbem-594 95 5 from from ADP fbem-594 95 6 the the DET fbem-594 95 7 figure figure NOUN fbem-594 95 8 that that SCONJ fbem-594 95 9 most most ADJ fbem-594 95 10 of of ADP fbem-594 95 11 the the DET fbem-594 95 12 14 14 NUM fbem-594 95 13 groups group NOUN fbem-594 95 14 of of ADP fbem-594 95 15 data datum NOUN fbem-594 95 16 are be AUX fbem-594 95 17 predicted predict VERB fbem-594 95 18 accurately accurately ADV fbem-594 95 19 . . PUNCT fbem-594 96 1 6 6 X fbem-594 96 2 . . X fbem-594 96 3 conclusion conclusion NOUN fbem-594 96 4 and and CCONJ fbem-594 96 5 prospect prospect NOUN fbem-594 96 6 firstly firstly ADV fbem-594 96 7 , , PUNCT fbem-594 96 8 this this DET fbem-594 96 9 paper paper NOUN fbem-594 96 10 investigates investigate VERB fbem-594 96 11 the the DET fbem-594 96 12 actual actual ADJ fbem-594 96 13 intersection intersection NOUN fbem-594 96 14 , , PUNCT fbem-594 96 15 obtains obtain VERB fbem-594 96 16 the the DET fbem-594 96 17 hourly hourly ADJ fbem-594 96 18 traffic traffic NOUN fbem-594 96 19 volume volume NOUN fbem-594 96 20 in in ADP fbem-594 96 21 all all DET fbem-594 96 22 directions direction NOUN fbem-594 96 23 of of ADP fbem-594 96 24 each each DET fbem-594 96 25 entrance entrance NOUN fbem-594 96 26 lane lane NOUN fbem-594 96 27 of of ADP fbem-594 96 28 the the DET fbem-594 96 29 intersection intersection NOUN fbem-594 96 30 and and CCONJ fbem-594 96 31 the the DET fbem-594 96 32 signal signal ADJ fbem-594 96 33 timing timing NOUN fbem-594 96 34 of of ADP fbem-594 96 35 each each DET fbem-594 96 36 phase phase NOUN fbem-594 96 37 of of ADP fbem-594 96 38 the the DET fbem-594 96 39 intersection intersection NOUN fbem-594 96 40 , , PUNCT fbem-594 96 41 then then ADV fbem-594 96 42 inputs input VERB fbem-594 96 43 the the DET fbem-594 96 44 survey survey NOUN fbem-594 96 45 data datum NOUN fbem-594 96 46 into into ADP fbem-594 96 47 the the DET fbem-594 96 48 vissim vissim PROPN fbem-594 96 49 simulation simulation PROPN fbem-594 96 50 model model PROPN fbem-594 96 51 , , PUNCT fbem-594 96 52 simulates simulate VERB fbem-594 96 53 the the DET fbem-594 96 54 motor motor NOUN fbem-594 96 55 vehicles vehicle NOUN fbem-594 96 56 at at ADP fbem-594 96 57 the the DET fbem-594 96 58 intersection intersection NOUN fbem-594 96 59 for for ADP fbem-594 96 60 one one NUM fbem-594 96 61 hour hour NOUN fbem-594 96 62 based base VERB fbem-594 96 63 on on ADP fbem-594 96 64 vissim vissim PROPN fbem-594 96 65 simulation simulation PROPN fbem-594 96 66 , , PUNCT fbem-594 96 67 obtains obtain VERB fbem-594 96 68 the the DET fbem-594 96 69 simulation simulation NOUN fbem-594 96 70 data datum NOUN fbem-594 96 71 , , PUNCT fbem-594 96 72 and and CCONJ fbem-594 96 73 puts put VERB fbem-594 96 74 forward forward ADV fbem-594 96 75 the the DET fbem-594 96 76 traffic traffic NOUN fbem-594 96 77 flow flow NOUN fbem-594 96 78 direction direction NOUN fbem-594 96 79 prediction prediction NOUN fbem-594 96 80 method method NOUN fbem-594 96 81 based base VERB fbem-594 96 82 on on ADP fbem-594 96 83 knn knn PROPN fbem-594 96 84 algorithm algorithm PROPN fbem-594 96 85 , , PUNCT fbem-594 96 86 the the DET fbem-594 96 87 results result NOUN fbem-594 96 88 show show VERB fbem-594 96 89 that that SCONJ fbem-594 96 90 the the DET fbem-594 96 91 predicted predict VERB fbem-594 96 92 traffic traffic NOUN fbem-594 96 93 flow flow NOUN fbem-594 96 94 direction direction NOUN fbem-594 96 95 has have AUX fbem-594 96 96 achieved achieve VERB fbem-594 96 97 good good ADJ fbem-594 96 98 results result NOUN fbem-594 96 99 . . PUNCT fbem-594 97 1 the the DET fbem-594 97 2 prediction prediction NOUN fbem-594 97 3 results result NOUN fbem-594 97 4 of of ADP fbem-594 97 5 this this DET fbem-594 97 6 paper paper NOUN fbem-594 97 7 can can AUX fbem-594 97 8 provide provide VERB fbem-594 97 9 reference reference NOUN fbem-594 97 10 information information NOUN fbem-594 97 11 for for ADP fbem-594 97 12 a a DET fbem-594 97 13 large large ADJ fbem-594 97 14 number number NOUN fbem-594 97 15 of of ADP fbem-594 97 16 urban urban ADJ fbem-594 97 17 driving drive VERB fbem-594 97 18 road road NOUN fbem-594 97 19 selection selection NOUN fbem-594 97 20 , , PUNCT fbem-594 97 21 timely timely ADV fbem-594 97 22 understand understand VERB fbem-594 97 23 the the DET fbem-594 97 24 direction direction NOUN fbem-594 97 25 of of ADP fbem-594 97 26 traffic traffic NOUN fbem-594 97 27 flow flow NOUN fbem-594 97 28 , , PUNCT fbem-594 97 29 reduce reduce VERB fbem-594 97 30 the the DET fbem-594 97 31 probability probability NOUN fbem-594 97 32 of of ADP fbem-594 97 33 entering enter VERB fbem-594 97 34 congested congested ADJ fbem-594 97 35 traffic traffic NOUN fbem-594 97 36 flow flow NOUN fbem-594 97 37 , , PUNCT fbem-594 97 38 and and CCONJ fbem-594 97 39 provide provide VERB fbem-594 97 40 relevant relevant ADJ fbem-594 97 41 decision decision NOUN fbem-594 97 42 - - PUNCT fbem-594 97 43 making make VERB fbem-594 97 44 information information NOUN fbem-594 97 45 for for ADP fbem-594 97 46 urban urban ADJ fbem-594 97 47 traffic traffic NOUN fbem-594 97 48 managers manager NOUN fbem-594 97 49 . . PUNCT fbem-594 98 1 due due ADP fbem-594 98 2 to to ADP fbem-594 98 3 the the DET fbem-594 98 4 small small ADJ fbem-594 98 5 amount amount NOUN fbem-594 98 6 of of ADP fbem-594 98 7 data datum NOUN fbem-594 98 8 , , PUNCT fbem-594 98 9 although although SCONJ fbem-594 98 10 the the DET fbem-594 98 11 prediction prediction NOUN fbem-594 98 12 results result NOUN fbem-594 98 13 of of ADP fbem-594 98 14 this this DET fbem-594 98 15 paper paper NOUN fbem-594 98 16 have have AUX fbem-594 98 17 been be AUX fbem-594 98 18 considerable considerable ADJ fbem-594 98 19 , , PUNCT fbem-594 98 20 they they PRON fbem-594 98 21 are be AUX fbem-594 98 22 not not PART fbem-594 98 23 particularly particularly ADV fbem-594 98 24 reliable reliable ADJ fbem-594 98 25 . . PUNCT fbem-594 99 1 in in ADP fbem-594 99 2 the the DET fbem-594 99 3 next next ADJ fbem-594 99 4 research research NOUN fbem-594 99 5 , , PUNCT fbem-594 99 6 we we PRON fbem-594 99 7 can can AUX fbem-594 99 8 use use VERB fbem-594 99 9 a a DET fbem-594 99 10 large large ADJ fbem-594 99 11 number number NOUN fbem-594 99 12 of of ADP fbem-594 99 13 traffic traffic NOUN fbem-594 99 14 flow flow NOUN fbem-594 99 15 data datum NOUN fbem-594 99 16 , , PUNCT fbem-594 99 17 such such ADJ fbem-594 99 18 as as ADP fbem-594 99 19 traffic traffic NOUN fbem-594 99 20 flow flow NOUN fbem-594 99 21 data datum NOUN fbem-594 99 22 for for ADP fbem-594 99 23 3 3 NUM fbem-594 99 24 ~ ~ SYM fbem-594 99 25 5 5 NUM fbem-594 99 26 days day NOUN fbem-594 99 27 , , PUNCT fbem-594 99 28 to to PART fbem-594 99 29 further far ADV fbem-594 99 30 improve improve VERB fbem-594 99 31 the the DET fbem-594 99 32 authenticity authenticity NOUN fbem-594 99 33 of of ADP fbem-594 99 34 the the DET fbem-594 99 35 prediction prediction NOUN fbem-594 99 36 results result NOUN fbem-594 99 37 . . PUNCT fbem-594 100 1 this this DET fbem-594 100 2 paper paper NOUN fbem-594 100 3 forecasts forecast VERB fbem-594 100 4 the the DET fbem-594 100 5 traffic traffic NOUN fbem-594 100 6 flow flow NOUN fbem-594 100 7 direction direction NOUN fbem-594 100 8 based base VERB fbem-594 100 9 on on ADP fbem-594 100 10 vissim vissim PROPN fbem-594 100 11 simulation simulation PROPN fbem-594 100 12 . . PUNCT fbem-594 101 1 due due ADP fbem-594 101 2 to to ADP fbem-594 101 3 the the DET fbem-594 101 4 difference difference NOUN fbem-594 101 5 between between ADP fbem-594 101 6 the the DET fbem-594 101 7 actual actual ADJ fbem-594 101 8 traffic traffic NOUN fbem-594 101 9 condition condition NOUN fbem-594 101 10 and and CCONJ fbem-594 101 11 the the DET fbem-594 101 12 simulated simulated ADJ fbem-594 101 13 traffic traffic NOUN fbem-594 101 14 condition condition NOUN fbem-594 101 15 , , PUNCT fbem-594 101 16 the the DET fbem-594 101 17 actual actual ADJ fbem-594 101 18 traffic traffic NOUN fbem-594 101 19 flow flow NOUN fbem-594 101 20 data datum NOUN fbem-594 101 21 can can AUX fbem-594 101 22 be be AUX fbem-594 101 23 used use VERB fbem-594 101 24 to to PART fbem-594 101 25 predict predict VERB fbem-594 101 26 the the DET fbem-594 101 27 traffic traffic NOUN fbem-594 101 28 flow flow NOUN fbem-594 101 29 direction direction NOUN fbem-594 101 30 in in ADP fbem-594 101 31 the the DET fbem-594 101 32 next next ADJ fbem-594 101 33 research research NOUN fbem-594 101 34 , , PUNCT fbem-594 101 35 so so SCONJ fbem-594 101 36 as as SCONJ fbem-594 101 37 to to PART fbem-594 101 38 further far ADV fbem-594 101 39 improve improve VERB fbem-594 101 40 the the DET fbem-594 101 41 practicability practicability NOUN fbem-594 101 42 of of ADP fbem-594 101 43 the the DET fbem-594 101 44 prediction prediction NOUN fbem-594 101 45 results result NOUN fbem-594 101 46 . . PUNCT fbem-594 102 1 references reference NOUN fbem-594 102 2 [ [ X fbem-594 102 3 1 1 NUM fbem-594 102 4 ] ] X fbem-594 102 5 yang yang PROPN fbem-594 102 6 , , PUNCT fbem-594 102 7 hai hai PROPN fbem-594 102 8 , , PUNCT fbem-594 102 9 wolfson wolfson PROPN fbem-594 102 10 , , PUNCT fbem-594 102 11 et et PROPN fbem-594 102 12 al al PROPN fbem-594 102 13 . . PUNCT fbem-594 103 1 urban urban PROPN fbem-594 103 2 computing computing PROPN fbem-594 103 3 : : PUNCT fbem-594 103 4 concepts concept NOUN fbem-594 103 5 , , PUNCT fbem-594 103 6 methodologies methodology NOUN fbem-594 103 7 , , PUNCT fbem-594 103 8 and and CCONJ fbem-594 103 9 applications[j applications[j PROPN fbem-594 103 10 ] ] PUNCT fbem-594 103 11 . . PUNCT fbem-594 104 1 acm acm PROPN fbem-594 104 2 transactions transaction NOUN fbem-594 104 3 on on ADP fbem-594 104 4 intelligent intelligent ADJ fbem-594 104 5 systems system NOUN fbem-594 104 6 and and CCONJ fbem-594 104 7 technology technology NOUN fbem-594 104 8 , , PUNCT fbem-594 104 9 2014 2014 NUM fbem-594 104 10 , , PUNCT fbem-594 104 11 5(3):38.1 5(3):38.1 NUM fbem-594 104 12 - - SYM fbem-594 104 13 38.55 38.55 NUM fbem-594 104 14 . . PUNCT fbem-594 105 1 [ [ X fbem-594 105 2 2 2 NUM fbem-594 105 3 ] ] PUNCT fbem-594 105 4 pan pan NOUN fbem-594 105 5 g g PROPN fbem-594 105 6 , , PUNCT fbem-594 105 7 qi qi PROPN fbem-594 105 8 g g PROPN fbem-594 105 9 , , PUNCT fbem-594 105 10 zhang zhang PROPN fbem-594 105 11 w w PROPN fbem-594 105 12 , , PUNCT fbem-594 105 13 et et PROPN fbem-594 105 14 al al PROPN fbem-594 105 15 . . PROPN fbem-594 105 16 trace trace NOUN fbem-594 105 17 analysis analysis NOUN fbem-594 105 18 and and CCONJ fbem-594 105 19 mining mining NOUN fbem-594 105 20 for for ADP fbem-594 105 21 smart smart ADJ fbem-594 105 22 cities city NOUN fbem-594 105 23 : : PUNCT fbem-594 105 24 issues issue NOUN fbem-594 105 25 , , PUNCT fbem-594 105 26 methods method NOUN fbem-594 105 27 , , PUNCT fbem-594 105 28 and and CCONJ fbem-594 105 29 applications[j applications[j PROPN fbem-594 105 30 ] ] PUNCT fbem-594 105 31 . . PUNCT fbem-594 106 1 ieee ieee PROPN fbem-594 106 2 communications communications PROPN fbem-594 106 3 magazine magazine NOUN fbem-594 106 4 , , PUNCT fbem-594 106 5 2013 2013 NUM fbem-594 106 6 , , PUNCT fbem-594 106 7 51(6):120 51(6):120 NOUN fbem-594 106 8 - - SYM fbem-594 106 9 126 126 NUM fbem-594 106 10 . . PUNCT fbem-594 107 1 [ [ X fbem-594 107 2 3 3 X fbem-594 107 3 ] ] X fbem-594 107 4 x x X fbem-594 107 5 zheng zheng PROPN fbem-594 107 6 , , PUNCT fbem-594 107 7 w w PROPN fbem-594 107 8 chen chen PROPN fbem-594 107 9 , , PUNCT fbem-594 107 10 p p PROPN fbem-594 107 11 wang wang PROPN fbem-594 107 12 , , PUNCT fbem-594 107 13 etc etc X fbem-594 107 14 . . X fbem-594 107 15 big big ADJ fbem-594 107 16 data datum NOUN fbem-594 107 17 for for ADP fbem-594 107 18 social social ADJ fbem-594 107 19 transportation[j transportation[j NOUN fbem-594 107 20 ] ] PUNCT fbem-594 107 21 . . PUNCT fbem-594 108 1 ieee ieee NOUN fbem-594 108 2 transactions transaction NOUN fbem-594 108 3 on on ADP fbem-594 108 4 intelligent intelligent ADJ fbem-594 108 5 transportation transportation NOUN fbem-594 108 6 systems system NOUN fbem-594 108 7 , , PUNCT fbem-594 108 8 2016 2016 NUM fbem-594 108 9 , , PUNCT fbem-594 108 10 17 17 NUM fbem-594 108 11 ( ( PUNCT fbem-594 108 12 3 3 NUM fbem-594 108 13 ): ): PUNCT fbem-594 108 14 620 620 NUM fbem-594 108 15 - - SYM fbem-594 108 16 630 630 NUM fbem-594 108 17 . . PUNCT fbem-594 109 1 [ [ X fbem-594 109 2 4 4 NUM fbem-594 109 3 ] ] X fbem-594 109 4 jenelius jenelius PROPN fbem-594 109 5 , , PUNCT fbem-594 109 6 erik erik PROPN fbem-594 109 7 , , PUNCT fbem-594 109 8 rahmani rahmani PROPN fbem-594 109 9 , , PUNCT fbem-594 109 10 et et PROPN fbem-594 109 11 al al PROPN fbem-594 109 12 . . PUNCT fbem-594 110 1 non non ADJ fbem-594 110 2 - - ADJ fbem-594 110 3 parametric parametric ADJ fbem-594 110 4 estimation estimation NOUN fbem-594 110 5 of of ADP fbem-594 110 6 route route NOUN fbem-594 110 7 travel travel NOUN fbem-594 110 8 time time NOUN fbem-594 110 9 distributions distribution NOUN fbem-594 110 10 from from ADP fbem-594 110 11 low low ADJ fbem-594 110 12 - - PUNCT fbem-594 110 13 frequency frequency NOUN fbem-594 110 14 floating float VERB fbem-594 110 15 car car NOUN fbem-594 110 16 data datum NOUN fbem-594 111 1 [ [ X fbem-594 111 2 j j X fbem-594 111 3 ] ] X fbem-594 111 4 . . PUNCT fbem-594 112 1 transportation transportation NOUN fbem-594 112 2 research research NOUN fbem-594 112 3 part part NOUN fbem-594 112 4 c c NOUN fbem-594 112 5 emerging emerge VERB fbem-594 112 6 technologies technology NOUN fbem-594 112 7 , , PUNCT fbem-594 112 8 2015 2015 NUM fbem-594 112 9 . . PUNCT fbem-594 113 1 [ [ X fbem-594 113 2 5 5 X fbem-594 113 3 ] ] X fbem-594 113 4 robinson robinson PROPN fbem-594 113 5 s s PROPN fbem-594 113 6 , , PUNCT fbem-594 113 7 polak polak PROPN fbem-594 113 8 j j PROPN fbem-594 113 9 . . PUNCT fbem-594 114 1 modeling model VERB fbem-594 114 2 urban urban PROPN fbem-594 114 3 link link NOUN fbem-594 114 4 travel travel NOUN fbem-594 114 5 time time NOUN fbem-594 114 6 with with ADP fbem-594 114 7 inductive inductive ADJ fbem-594 114 8 loop loop NOUN fbem-594 114 9 detector detector NOUN fbem-594 114 10 data datum NOUN fbem-594 114 11 by by ADP fbem-594 114 12 using use VERB fbem-594 114 13 the the DET fbem-594 114 14 k k PROPN fbem-594 114 15 - - PUNCT fbem-594 114 16 nn nn ADJ fbem-594 114 17 method[j method[j PROPN fbem-594 114 18 ] ] PUNCT fbem-594 114 19 . . PUNCT fbem-594 115 1 transportation transportation NOUN fbem-594 115 2 research research NOUN fbem-594 115 3 record record NOUN fbem-594 115 4 journal journal NOUN fbem-594 115 5 of of ADP fbem-594 115 6 the the DET fbem-594 115 7 transportation transportation NOUN fbem-594 115 8 research research NOUN fbem-594 115 9 board board NOUN fbem-594 115 10 , , PUNCT fbem-594 115 11 2005 2005 NUM fbem-594 115 12 , , PUNCT fbem-594 115 13 1935:47 1935:47 NUM fbem-594 115 14 - - SYM fbem-594 115 15 56 56 NUM fbem-594 115 16 . . PUNCT fbem-594 116 1 [ [ X fbem-594 116 2 6 6 X fbem-594 116 3 ] ] X fbem-594 116 4 lim lim PROPN fbem-594 116 5 s s PROPN fbem-594 116 6 h h NOUN fbem-594 116 7 , , PUNCT fbem-594 116 8 lee lee PROPN fbem-594 116 9 h h PROPN fbem-594 116 10 m m PROPN fbem-594 116 11 , , PUNCT fbem-594 116 12 paο½’k paο½’k PROPN fbem-594 116 13 s s PROPN fbem-594 116 14 l l NOUN fbem-594 116 15 , , PUNCT fbem-594 116 16 et et PROPN fbem-594 116 17 al al PROPN fbem-594 116 18 . . PUNCT fbem-594 117 1 a a DET fbem-594 117 2 study study NOUN fbem-594 117 3 of of ADP fbem-594 117 4 traveltime traveltime NOUN fbem-594 117 5 prediction prediction NOUN fbem-594 117 6 using use VERB fbem-594 117 7 k k NOUN fbem-594 117 8 - - PUNCT fbem-594 117 9 nearest near ADJ fbem-594 117 10 neighborhood neighborhood NOUN fbem-594 117 11 method method NOUN fbem-594 118 1 [ [ X fbem-594 118 2 j j X fbem-594 118 3 ] ] X fbem-594 118 4 . . PUNCT fbem-594 119 1 korean korean ADJ fbem-594 119 2 journal journal PROPN fbem-594 119 3 of of ADP fbem-594 119 4 applied applied ADJ fbem-594 119 5 statistics statistic NOUN fbem-594 119 6 , , PUNCT fbem-594 119 7 2013 2013 NUM fbem-594 119 8 , , PUNCT fbem-594 119 9 26(5 26(5 NUM fbem-594 119 10 ) ) PUNCT fbem-594 119 11 : : PUNCT fbem-594 119 12 835 835 NUM fbem-594 119 13 -845 -845 NOUN fbem-594 119 14 . . PUNCT