基于Elman组合预测模型的瓦斯涌出量预测  

Amount of gas emission prediction base on Elman and combination prediction model

作　　者：王春晓[1] 陈开岩[1] 张宝[1] 

机构地区：[1]中国矿业大学安全工程学院,江苏徐州221116

出　　处：《黑龙江科技学院学报》2011年第4期285-288,共4页Journal of Heilongjiang Institute of Science and Technology

摘　　要：为提高矿井瓦斯涌出量的预测精度,基于Elman回归神经网络原理,以指数型线性回归、双曲线型线性回归及灰色预测三种方法得到的瓦斯涌出量预测值为样本数据,建立Elman组合预测模型,并利用MATLAB软件进行预测。结果表明,Elman组合预测结果的拟合曲线更接近实际情况。该模型有效提高了瓦期涌出量的预测精度,为煤矿安全生产提供了理论支持。Aimed at improving the accuracy of gas emission prediction,this paper introduces an Elman neural network,that is combination prediction,based on the prediction got from hyperbola function,exponent function and grey model as the sample data and according to the fundamental theory of the combination prediction and the Elman neural network and highlights prediction using MATLAB curve fitting tool.The result shows that the combination prediction is in accordance with practical case.This model,marked by an effective improvement in the accuracy of the predictions,provides theoretical support for the coal mine safety.

关 键 词：ELMAN神经网络 组合预测 瓦斯涌出量 

分 类 号：TD712[矿业工程—矿井通风与安全]