Intelligent Prediction System of Coal-Gas Outburst Based on Evolutionary Neural Nets

The novel coal-gas dangerous-level prediction model established has advantages of the EA and BP neural nets, and overcomes the shortcomings of misreport and missing-report of others. This approach can accurately capture the complicated relationships among feature values of coal-gas outbursts and dangerous circumstances. We considered the characteristic of coal-gas outburst carefully, combining with the raw data of coal-gas monitor system in the Daping colliery and the 10^th colliery of Pingdingshan Company as well as real-time samples of accidents, and selected pattern sets to train the proposed model and generate the corresponding rules for prediction. Results show that the ENN has better performance than the ANN or the traditional method used individually, and enhances the practical techniques for prediction of coal and gas in coal mine to guarantee safety.