工作面煤与瓦斯突出电磁辐射的神经网络预测方法研究  

Study on the electromagnetic emission neural network forecasting method of coal and gas outburst of working face

作　　者：撒占友[1] 何学秋[2] 王恩元[2] 

机构地区：[1]青岛建筑工程学院交通运输系,山东青岛266520 [2]中国矿业大学能源科学与工程学院,江苏徐州221008

出　　处：《煤炭学报》2004年第5期563-567,共5页Journal of China Coal Society

基　　金：国家杰出青年基金资助项目(59925411);国家自然科学基金资助项目(50134040;50204010)

摘　　要：以自适应神经网络的基本原理为基础,系统研究了煤与瓦斯突出电磁辐射自适应神经网络预测的原理,将电磁辐射自适应神经网络模型应用于煤与瓦斯突出危险性预测,实现了煤与瓦斯突出危险性的电磁辐射动态趋势预测.应用结果表明,煤与瓦斯突出电磁辐射神经网络预测法具有预测方法简单、准确性高等特点,可应用于工作面煤与瓦斯突出危险性的预测.Based on basic principle of self-adapting neural network, studied a principle of electromagnetic emission (EME) self-adapting neural network forecasting coal and gas outburst, and applied the method to forecast the danger of coal and gas outburst. It realized an EME dynamic trend forecast of the danger of coal and gas outburst. The application results show that the EME neural network forecasting method of coal and gas outburst has many characteristics of simple forecasting method, high accuracy, and so on. It is feasible to be applied to forecast the danger of coal and gas outburst.

关 键 词：煤与瓦斯突出 电磁辐射 神经网络 预测 

分 类 号：TD713[矿业工程—矿井通风与安全]