Application of Gray Elman Neural Network to Predict the Gas Emission Amount

Abstract

The prediction of mine Gas Emission Amount is an important part of helping to make rational gas control measures. In order to improve the accuracy of mine gas emission prediction, this paper introduced the grey theory into the Elman artificial neural network theory, and combined the gray prediction model GM (1,1) with the Elman neural network model,established a gray Elman artificial neural network prediction model of gas emission, and carried on the simulation through software Matlab. Practice and experiment showed that this method compared well, and is superior to the traditional Grey prediction model, moreover this method also applied to the situation of original data was few or the historical data had transition. The forecasting results from this method can be more reliable and accurate, so it can instruct the practice accurately