id	sid	eid	entity	type
fcis-24300	1	1	2832-6024	DATE
fcis-24300	2	1	9	CARDINAL
fcis-24300	2	2	1	CARDINAL
fcis-24300	2	3	2024 70	DATE
fcis-24300	2	4	di liang 1	PERSON
fcis-24300	2	5	zhongming lin 1	PERSON
fcis-24300	2	6	su 2	PERSON
fcis-24300	2	7	li 1	FAC
fcis-24300	2	8	biaotang wen 3	PERSON
fcis-24300	2	9	zhendong chen 4	PERSON
fcis-24300	2	10	yuanyuan guo 4	PERSON
fcis-24300	2	11	y.d.	GPE
fcis-24300	2	12	5 1	QUANTITY
fcis-24300	2	13	university	GPE
fcis-24300	2	14	nanning guangxi	GPE
fcis-24300	2	15	53000	CARDINAL
fcis-24300	2	16	china 2 school of languages	ORG
fcis-24300	2	17	liuzhou institute of technology	ORG
fcis-24300	2	18	liuzhou	GPE
fcis-24300	2	19	guangxi	GPE
fcis-24300	2	20	545616	DATE
fcis-24300	2	21	china 3	ORG
fcis-24300	2	22	jiejiarun technology group co., ltd	ORG
fcis-24300	2	23	nanning guangxi	GPE
fcis-24300	2	24	53000	CARDINAL
fcis-24300	2	25	china	GPE
fcis-24300	2	26	4	CARDINAL
fcis-24300	2	27	guangxi academy of	ORG
fcis-24300	2	28	nanning guangxi	GPE
fcis-24300	2	29	53000	CARDINAL
fcis-24300	2	30	china 5	ORG
fcis-24300	2	31	tunku abdul rahman university	PERSON
fcis-24300	2	32	53300	CARDINAL
fcis-24300	2	33	kuala lumpur	GPE
fcis-24300	2	34	malaysia	GPE
fcis-24300	2	35	di liang	PERSON
fcis-24300	9	1	1	CARDINAL
fcis-24300	16	1	1	CARDINAL
fcis-24300	20	1	2	CARDINAL
fcis-24300	21	1	2	CARDINAL
fcis-24300	22	1	2.1	CARDINAL
fcis-24300	23	1	four	CARDINAL
fcis-24300	23	2	71	CARDINAL
fcis-24300	24	1	1	CARDINAL
fcis-24300	26	1	3	CARDINAL
fcis-24300	27	1	seasons	DATE
fcis-24300	31	1	4	CARDINAL
fcis-24300	31	2	lora	PERSON
fcis-24300	32	1	2	CARDINAL
fcis-24300	34	1	5	CARDINAL
fcis-24300	36	1	3	CARDINAL
fcis-24300	41	1	cnn	ORG
fcis-24300	41	2	rnn	ORG
fcis-24300	43	1	2.2	CARDINAL
fcis-24300	44	1	1	CARDINAL
fcis-24300	46	1	6	CARDINAL
fcis-24300	48	1	2	CARDINAL
fcis-24300	52	1	3	CARDINAL
fcis-24300	52	2	cnn	ORG
fcis-24300	54	1	cnn	ORG
fcis-24300	58	1	72	CARDINAL
fcis-24300	59	1	2.3	CARDINAL
fcis-24300	66	1	2.4	CARDINAL
fcis-24300	67	1	1	CARDINAL
fcis-24300	69	1	8	CARDINAL
fcis-24300	71	1	2	CARDINAL
fcis-24300	71	2	three	CARDINAL
fcis-24300	75	1	9	CARDINAL
fcis-24300	78	1	3	CARDINAL
fcis-24300	84	1	3	CARDINAL
fcis-24300	84	2	3.1	CARDINAL
fcis-24300	87	1	two	CARDINAL
fcis-24300	87	2	one	CARDINAL
fcis-24300	90	1	one year	DATE
fcis-24300	91	1	73	CARDINAL
fcis-24300	93	1	3.2	CARDINAL
fcis-24300	96	1	10	CARDINAL
fcis-24300	99	1	0	CARDINAL
fcis-24300	99	2	1	CARDINAL
fcis-24300	101	1	4.	CARDINAL
fcis-24300	101	2	4.1	CARDINAL
fcis-24300	103	1	cnn	ORG
fcis-24300	104	1	1	CARDINAL
fcis-24300	107	1	70%	PERCENT
fcis-24300	107	2	15%	PERCENT
fcis-24300	107	3	15%	PERCENT
fcis-24300	108	1	100	CARDINAL
fcis-24300	108	2	10	CARDINAL
fcis-24300	108	3	2	CARDINAL
fcis-24300	109	1	#	CARDINAL
fcis-24300	109	2	x_train	CARDINAL
fcis-24300	109	3	y_train	ORG
fcis-24300	109	4	#	CARDINAL
fcis-24300	109	5	=randomforestregressor(n_estimators=100,max_dept h=10,min_samples_split=2	ORG
fcis-24300	111	1	50	CARDINAL
fcis-24300	111	2	100	CARDINAL
fcis-24300	111	3	150	CARDINAL
fcis-24300	112	1	10	CARDINAL
fcis-24300	112	2	15	DATE
fcis-24300	112	3	20	CARDINAL
fcis-24300	113	1	2	CARDINAL
fcis-24300	113	2	5	DATE
fcis-24300	113	3	10	CARDINAL
fcis-24300	113	4	n_jobs=-1	ORG
fcis-24300	113	5	#	CARDINAL
fcis-24300	114	1	mse	ORG
fcis-24300	116	1	0.015	CARDINAL
fcis-24300	116	2	0.92	CARDINAL
fcis-24300	117	1	4.2	CARDINAL
fcis-24300	118	1	cnn	ORG
fcis-24300	118	2	cnn	ORG
fcis-24300	120	1	74	CARDINAL
fcis-24300	123	1	70%	PERCENT
fcis-24300	123	2	15%	PERCENT
fcis-24300	123	3	15%	PERCENT
fcis-24300	124	1	cnn	ORG
fcis-24300	124	2	3	CARDINAL
fcis-24300	124	3	2	CARDINAL
fcis-24300	124	4	2	CARDINAL
fcis-24300	126	1	keras.models	ORG
fcis-24300	126	2	maxpooling2d	GPE
fcis-24300	126	3	#	CARDINAL
fcis-24300	126	4	1	CARDINAL
fcis-24300	126	5	#	CARDINAL
fcis-24300	126	6	model.compile(optimizer='adam',loss='binary_crossentrop y',metrics=('accuracy'l	ORG
fcis-24300	127	1	cnn	ORG
fcis-24300	127	2	0.001	CARDINAL
fcis-24300	127	3	32	CARDINAL
fcis-24300	127	4	50	CARDINAL
fcis-24300	128	1	epochs=50	GPE
fcis-24300	128	2	32,validation_data=(x_val	CARDINAL
fcis-24300	131	1	cnn	ORG
fcis-24300	131	2	0.95	CARDINAL
fcis-24300	132	1	5	CARDINAL
fcis-24300	139	1	the department of science and technology	ORG
fcis-24300	139	2	guangxi zhuang	GPE
fcis-24300	140	1	2024	CARDINAL
fcis-24300	140	2	10	CARDINAL
fcis-24300	143	1	hebei agriculture	GPE
fcis-24300	143	2	2024	DATE
fcis-24300	143	3	05	CARDINAL
fcis-24300	143	4	44-46	DATE
fcis-24300	144	1	2	CARDINAL
fcis-24300	146	1	hebei agricultural machinery	ORG
fcis-24300	146	2	2024,(09);2830.doi:10.15989/j.cnki.hbnjzzs.2024.09.031	ORG
fcis-24300	147	1	3	CARDINAL
fcis-24300	149	1	2024	CARDINAL
fcis-24300	149	2	55	DATE
fcis-24300	149	3	09	CARDINAL
fcis-24300	149	4	56	CARDINAL
fcis-24300	150	1	4	CARDINAL
fcis-24300	150	2	wu lian	PERSON
fcis-24300	150	3	wang xue	PERSON
fcis-24300	151	1	2024	DATE
fcis-24300	151	2	14	DATE
fcis-24300	151	3	03	CARDINAL
fcis-24300	151	4	98	CARDINAL
fcis-24300	152	1	10.16667	CARDINAL
fcis-24300	153	1	03.023	CARDINAL
fcis-24300	154	1	5	CARDINAL
fcis-24300	156	1	2024	DATE
fcis-24300	156	2	11-13	DATE
fcis-24300	157	1	6	CARDINAL
fcis-24300	159	1	2024,44(08).17-18.doi:10.16815	ORG
fcis-24300	159	2	0 03	CARDINAL
fcis-24300	160	1	7	CARDINAL
fcis-24300	162	1	2024	CARDINAL
fcis-24300	162	2	53	DATE
fcis-24300	162	3	01	DATE
fcis-24300	162	4	274-275	CARDINAL
fcis-24300	163	1	8	CARDINAL
fcis-24300	163	2	the organic promotion of ai	ORG
fcis-24300	164	1	shanxi science and technology news	ORG
fcis-24300	164	2	2024.01.08	DATE
fcis-24300	165	1	5	CARDINAL
fcis-24300	166	1	guangxi communication technology	ORG
fcis-24300	166	2	2023	CARDINAL
fcis-24300	166	3	04	CARDINAL
fcis-24300	166	4	39-44	DATE
fcis-24300	167	1	10	CARDINAL
fcis-24300	167	2	xu	PERSON
fcis-24300	169	1	age 2021	DATE
fcis-24300	169	2	1-3 +7	QUANTITY
fcis-24300	170	1	10.16644	CARDINAL