煤层底板突水危险性预测的熵权-正态云模型

doi:10.16265/j.cnki.issn1003-3033.2022.S1.0445

中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (S1): 171-177.doi: 10.16265/j.cnki.issn1003-3033.2022.S1.0445

煤层底板突水危险性预测的熵权-正态云模型

马天行¹(), 林允¹^,²^,^**(), 周晓斌¹, 魏培荣¹, 李仁宗³, 苏家玉³

¹ 中南大学资源与安全工程学院, 湖南长沙 410083
² 山东科技大学矿山岩层智能控制与绿色开采省部共建国家重点实验室培育基地, 山东青岛 266590
³ 中南大学建筑与艺术学院, 湖南长沙 410083

收稿日期:2022-01-11 修回日期:2022-04-15 出版日期:2022-06-30 发布日期:2022-12-30
通讯作者: 林允
作者简介:
马天行 (2000—),男,山西阳泉人,本科,研究方向为岩土力学、地质灾害、智能防灾减灾。E-mail: 1297077298@qq.com。
基金资助:
国家自然科学基金资助(52104109); 省部共建矿山岩层智能控制与绿色开采国家重点实验室培育基地开放课题(SICGM202201); 中南大学大型仪器设备共享基金资助(CSUZC202211)

Entropy weight-normal cloud model for water inrush risk prediction of coal seam floor

MA Tianxing¹(), LIN Yun¹^,²^,^**(), ZHOU Xiaobin¹, WEI Peirong¹, LI Renzong³, SU Jiayu³

¹ School of Resources and Safety Engineering, Central South University, Changsha Hunan 410083, China
² State Key Laboratory of Strata Intelligent Control and Green Mining Co-founded by Shandong Province and the Ministry of Science and Technology, Shandong University of Science and Technology, Qingdao Shandong 266590, China
³ School of Architecture and Art, Central South University, Changsha Hunan 410083, China

Received:2022-01-11 Revised:2022-04-15 Online:2022-06-30 Published:2022-12-30
Contact: LIN Yun

摘要/Abstract

摘要：

为克服煤层底板突水危险性分级时的不确定性和模糊性,建立一种用于煤层底板突水危险性分级预测的熵权-正态云模型。选取13个影响因素构建评价指标体系,通过熵权法(EWM)得到各评价指标权重,利用正态云模型计算综合不确定度,进而得到预测结果,以肥城矿区的14个地质块段作为检测样本,预测底板突水危险性等级。结果表明:该模型的预测结果基本与实际情况相符,且较层次分析法(AHP)在预测准确性和误差上更具优势,准确性提高7.14%,平均绝对误差(MAE)、均方误差(MSE)、平均绝对百分比误差(MAPE)和均方根误差(RMSE)分别降低0.21、0.35、0.069、0.27。

关键词: 底板突水, 熵权法(EWM), 正态云模型, 分级预测, 危险性等级

Abstract:

In order to overcome the uncertainty and ambiguity in the risk classification, an entropy weight-normal cloud model was put forward for the risk classification prediction of floor water inrush in the coal seam. Thirteen influencing factors were selected to construct the evaluation index system, and the weights of each index were obtained by the EWM. The comprehensive uncertainty was calculated using the normal cloud model, and the prediction results were obtained. Fourteen geological blocks in the Feicheng mining area were used as test samples to detect them. The results show that the forecast of the model is basically in line with the actual situation, and it has advantages over AHP in forecast accuracy and error, with the accuracy increased by 7.14%. MAE, MSE, MAPE and RMSE are reduced by 0.21, 0.35, 0.069 and 0.27, respectively.

Key words: floor water invasion, entropy weight method (EWM), normal cloud model, hierarchical prediction, hazard level

马天行, 林允, 周晓斌, 魏培荣, 李仁宗, 苏家玉. 煤层底板突水危险性预测的熵权-正态云模型[J]. 中国安全科学学报, 2022, 32(S1): 171-177.

MA Tianxing, LIN Yun, ZHOU Xiaobin, WEI Peirong, LI Renzong, SU Jiayu. Entropy weight-normal cloud model for water inrush risk prediction of coal seam floor[J]. China Safety Science Journal, 2022, 32(S1): 171-177.

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危险性等级	地质构造条件		水文地质条件	底板隔水层条件			开采条件
危险性等级	S₁/(条·km^-2)	S₃/%	S₅/MPa	S₉/m	S₁₀/MPa	S₁₁/(条·m^-3)	S₁₂/m	S₁₃/m
Ⅰ级	>3	>50	>3	<30	<1	>20	>3	>800
Ⅱ级	2~3	30~50	2~3	30~50	1~2	10~20	2~3	600~800
Ⅲ级	1~2	10~30	1~2	50~70	2~3	3~10	1~2	400~600
Ⅳ级	<1	<10	<1	>70	>3	<3	<1	<400

危险性等级	赋值	地质构造条件		水文地质条件
危险性等级	赋值	S₂	S₄	S₆	S₇	S₈
Ⅰ级	1	明显	发育	高	发育	强
Ⅱ级	2	较明显	较发育	较高	较发育	较强
Ⅲ级	3	较不明显	发育中等	中	发育中等	较弱
Ⅳ级	4	不明显	发育较差	低	发育较差	弱

样本	地质构造参数				水文地质参数				底板隔水层参数			开采参数		预测结果	AHP 结果	实际级别
样本	S₁	S₂	S₃	S₄	S₅	S₆	S₇	S₈	S₉	S₁₀	S₁₁	S₁₂	S₁₃	Ⅰ	Ⅰ	Ⅰ
1	2.56	1	60	1	2.85	1	1	1	29.7	2.6	7.09	1.5	300	Ⅱ	Ⅱ	Ⅱ
2	2.56	1	19	1	2.5	2	1	1	29.7	2.6	7.09	1.75	300	Ⅱ	Ⅰ	Ⅱ
3	1.35	3	50	1	2.52	1	2	1	30.7	1.75	3.8	2	400	Ⅱ	Ⅱ	Ⅱ
4	1.35	3	10	1	2.55	1	2	1	30.7	1.75	3.8	2	500	Ⅲ	Ⅲ	Ⅲ
5	1.35	3	10	2	2.95	2	3	3	35	1.75	4	2.15	500	Ⅰ	Ⅱ	Ⅱ
6	2	1	20	2	2.45	1	1	1	33	2.1	6	2	100	Ⅲ	Ⅲ	Ⅲ
7	1.9	3	15	2	2.25	1	3	3	35	2.1	7.1	1.75	600	Ⅲ	Ⅰ	Ⅱ
8	1.82	2	18	2	1.65	2	1	1	33.4	2.1	6.9	1.75	190	Ⅲ	Ⅱ	Ⅱ
9	1.78	2	17	2	1.9	2	3	2	33.4	2.1	7.1	2	560	Ⅲ	Ⅲ	Ⅲ
10	0.5	2	16	2	1.8	2	3	3	35	2.1	7.1	1.2	300	Ⅲ	Ⅳ	Ⅲ
11	0.55	3	10	3	1.6	3	3	3	32	2.1	10.5	2.05	800	Ⅲ	Ⅲ	Ⅱ
12	1.53	1	10	1	0.9	2	2	1	42	1.33	10.5	1.5	400	Ⅲ	Ⅰ	Ⅲ
13	0.4	3	40	1	1.25	1	3	3	30.9	1.33	8.04	1.5	1 060	Ⅲ	Ⅰ	Ⅱ
14	1.72	2	15	1	1.2	3	1	1	33	1.33	8.04	1.5	160	Ⅰ	Ⅰ	Ⅰ

模型	MAE	MSE	MAPE	RMSE
云模型	0.29	0.29	0.145	0.53
AHP	0.50	0.64	0.214	0.80

煤层底板突水危险性预测的熵权-正态云模型

Entropy weight-normal cloud model for water inrush risk prediction of coal seam floor

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