BP网络模型在煤与瓦斯突出预测中的应用  

Application of BP Neural Network in Predication of the Coal and Gas Outburst

作　　者：李万武[1] 刘兴安 王海龙 

机构地区：[1]黑龙江科技学院,黑龙江哈尔滨150027 [2]黑龙江省德利能源公司,黑龙江七台河154600

出　　处：《实验室研究与探索》2009年第10期48-50,共3页Research and Exploration In Laboratory

基　　金：黑龙江省教育厅科学技术研究项目(11531332)

摘　　要：煤与瓦斯突出是一种极其复杂的瓦斯动力灾害现象。以突出前兆的非线性特征值为输入值,基于BP神经网络的煤与瓦斯突出非线性预测模型,可以智能化定量判识煤与瓦斯突出危险。自适应学习速率法加快了网络收敛速度,该模型通过Matlab工具实现。实验结果表明,基于BP神经网络的预测模型可靠,预测精度高,效果良好。Coal and gas outburst is a very complex dynamic gas disaster.A non-linear predicting model in which the input value is the value of non-linear characteristics before outburst portent,based on BP neural network,can intelligently quantitatively identify coal and gas outburst danger.Adaptive learning rate method can speed up the convergence rate of the network and the model is completed through the Matlab tool.The experimental result reveal that the prediction model based on BP neural network is reliable and has accurate results.

关 键 词：BP神经网络 煤与瓦斯突出 预测 评价 

分 类 号：TD712[矿业工程—矿井通风与安全]