Study on the Gas Content of Coal Seam based on the BP Neural Network
The prediction model for gas content in coal seam has been built based on the BP Neural Network to predict gas content accurately. And the model has been solved and forecasted by combining MATLAB programming with actual data. Moreover, the comparison analysis has been performed with the traditional prediction model based on multiple-regression. The results show that the non-linear gas content model related with basement buried depth and coal seam thickness etc could be established by utilizing the BP Neural Network. And its prediction accuracy and feasibility are better than the multiple-regression model. It is an ideal model for predicting gas content. It could provide some new ideas for the gas content prediction and the prevention and control for coal and gas outburst.
coal seam gas content BP Neural Network prediction coal and gas outburst
Zhang Jianqing
Faculty of Resource and Safety Engineering, China University of Mining & Technology, Beijing 100083, China Financial Assets Department of Shengli Oilfield Branch, Dongying 257001, China
国际会议
The First International Symposium on Mine Safety Science and Engineering (首届矿山安全科学与工程学术会议)
北京
英文
1484-1492
2011-10-27（万方平台首次上网日期，不代表论文的发表时间）