安阳矿区煤与瓦斯突出预测模型的建立与应用

利用灰色关联分析法确定控制矿井煤与瓦斯突出的主导因素,根据人工神经网络建立煤与瓦斯突出危险性预测的系统结构,在此基础上,选用突出矿井的15个煤与瓦斯突出实例作为学习样本对网络进行训练,最后运用3个煤与瓦斯突出实例作为预测样本对所建模型进行验证。结果表明利用灰色理论—神经网络方法建立的预测模型能够满足煤与瓦斯突出预测的要求。通过分析和计算安阳矿区煤层的开采深度、地质构造(尤其是断层)与突出危险程度关系密切,在煤与瓦斯突出的预测、防治工作中可以作为首选指标来考虑。

Modeling and Application of Coal and Gas Outburst Prediction Model in Anyang Mining Area

Through the use of gray relationship analysis to determine the dominant factors controlling coalmine coal and gas outburst,based on artificial neural network establishes systematic structure to predict coal and gas outburst.On this basis,15 examples of coal and gas outburst in coalmines have selected as learning samples to train the network.Finally apply 3 coal and gas outbursts as prediction samples on the model built to carry out verification.The result has demonstrated that the prediction model established through the use of gray theory-neural network method can satisfy requirements of coal and gas outburst prediction.Through analysis and computation have found that the coal seam mining depth,geological structure（especially fault） in the Anyang mining area are closely related to outburst hazard level,thus these indices can be the preferred in coal and gas outburst prediction and control.