基于BP神经网络预测袁店一矿101、102采区10煤层底板突水量  

Prediction of 10 Seam in the No.101, 102 Winning Districts in the Yuanyi Coal Mine Based on BP Neural Network

作　　者：王腾辉[1] 王来斌[1] 王健[1] 孟令普 

机构地区：[1]安徽理工大学地球与环境学院,安徽淮南232001

出　　处：《山东工业技术》2014年第1期179-180,共2页Journal of Shandong Industrial Technology

摘　　要：运用用突水系数法进行突水危险性预测，再通过分析工作面的水压、含水层、隔水层厚度（底板岩层厚度）、底板采动破坏深度、断层落差（对完整底板而言断层落差取零）作为预测底板突水的控制参数建立BP神经网络模型进行底板突水量预测．以达到安全开采该采区10煤层的目的．With the information of 10 seam in the No.101, 102 winning districts in the Yuandian Yuanyi coal mine in Huaibei coal mining area, Application of water inrush coefficient method to predict the water inrush risk,Through the analysis of working face water, aquifer, aquiclude thickness （the thickness of rock bottom）, coal seam floor failure depth, the fault throw（for complete floor, the fault throw and zero）as the control parameter prediction of water inrush from floor to establish the BP neural network model for predicting water inrush, in order to achieve the safe mining of the mining area of 10 coal seam the purpose of.

关 键 词：突水系数法 BP神经网络 底板突水量 

分 类 号：TD745.21[矿业工程—矿井通风与安全]