基于灰色神经网络预测潘一东矿瓦斯含量

Gas Content Prediction of Panyi East Coal Mine Based on Gray Neural Network

运用灰色关联分析影响潘一东矿井瓦斯含量的各因素,得出煤层标高、顶板岩性、煤厚、地质构造是影响瓦斯赋存的主要因素。选取这四种因素作为神经网络的神经元进行建模预测,结果表明,基于灰色关联度的神经网络模型预测瓦斯含量,预测精度高,证明了基于灰色理论与神经网络预测模型的可靠性。

This paper analyses the factors affect gas content of Panyi East Coal Mine with grey relationship analysis method,the research results show that seam elevation,roof lithology,coal thickness and geological structure are the main factors that affect gas occurrence situation.The paper selects these four factors as neurons of neural network to build model and predict,the results reveal that neural network model based on grey relational grade has a high precision of predicting gas content,which certify the reliability of prediction model based on grey theory and neural network.