灰色Elman神经网络的矿井瓦斯涌出量预测

为了准确预测矿井瓦斯涌出量,将灰色理论与Elman神经网络模型结合,建立矿井瓦斯涌出量预测模型。灰色系统能较好地预测变化的趋势,而Elman神经网络具有动态特性好、逼近速度快、精度高等特点。对于煤矿生产中瓦斯涌出量的预测,两者结合能够发挥各自的优势,以某煤矿矿井为例,影响瓦斯涌出量的因素为预测因子建立灰色理论与Elman神经网络融合的预测模型。结果表明,灰色Elman神经网络模型优于传统灰色预测模型,提高了预测精度,达到了很好的预测效果。

Prediction of Mine Gas Emission of Gray Elman Neural Network

In order to accurately predict the amount of mine gas emission,the gray theory and Elman neural network model are combined to establish prediction model of mine gas emission.The gray system can predict the trend better,and the Elman neural network has good dynamic performance,quick convergence,high accuracy.For the prediction of gas emission in coal production,combination of the two can play their respective advantages,take a coal mine as an example,influence factors of gas emission as prediction factor to establish forecasting model of gray theory and Elman neural network fusion.The results show that,the gray Elman neural network model is better than the conventional gray forecasting model,improving the prediction accuracy,the prediction effect is very good.