煤矿安全2012，Vol.43Issue(10)：11-14,4.
基于拟牛顿优化算法BP神经网络的瓦斯灾害预测模型
Prediction Model of Gas Disaster Based on Quasi-Newton Algorithm BP Neural Network
摘要
Abstract
The forecasting of gas outburst and explosion accidents is one of the most pressing problem in current China's coal mine safety production.Introducing the Quasi-Newton optimization algorithm of BP neural network,this paper discusses the mathematical model,network architecture and programming design of establishing the gas disaster forecasting model of Quasi-Newton optimization algorithm BP neural network under the premise of keeping the relationship among the spatial entities and their distributions,and an instance of Jining No.2 coal mine is tested.The result shows that this model is stable,fast and high prediction accuracy,which can simulate the mine gas outburst and explosion accidents characteristics and make more accurate predictions on the gas disaster.关键词
瓦斯灾害/BP神经网络/拟牛顿优化算法/预测模型Key words
gas disaster/BP neural network/Quasi-Newton algorithm/prediction model分类
矿业与冶金引用本文复制引用
戴洪磊,韩李涛,陈传法..基于拟牛顿优化算法BP神经网络的瓦斯灾害预测模型[J].煤矿安全,2012,43(10):11-14,4.基金项目
山东省＇泰山学者＇建设工程专项经费资助项目 （）
