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

作　　者：马天行 林允[1,2] 周晓斌 魏培荣 李仁宗 苏家玉 MA Tianxing;LIN Yun;ZHOU Xiaobin;WEI Peirong;LI Renzong;SU Jiayu(School of Resources and Safety Engineering,Central South University,Changsha Hunan 410083,China;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;School of Architecture and Art,Central South University,Changsha Hunan 410083,China)

机构地区：[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

出　　处：《中国安全科学学报》2022年第S01期171-177,共7页China Safety Science Journal

基　　金：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)。

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。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.

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 

分 类 号：X936[环境科学与工程—安全科学]