The Method Of Classification Of Coal And Gas Outburst Dangerous Mines Based On The Neural Network

With analyzing the instance of mines outburst, think those is different in our country, therefore, there is necessity divides coal and gas outburst dangerous grade. Based on the extensive study of Huainan and Pingdingshan diggings, we got the outburst data for evaluating mine outburst dangerous degree. We educed the probability index by analyzing outburst happening condition and rule, educed the fatalness by analyzing it. Discussed the influence of safe invest in prevention coal and gas outburst and imported it into the evaluation model. Divided outburst mines into weak, medium, and serious outburst, thereby brought up evaluation system.Applying the method towards important and dangerous evaluate, deduced out the evaluation model. Applying the methods of gray system synthesize evaluation and proof theories, bring up to the dangerous degree measure (dangerous believe degree), and divide the outburst dangerous grade of coal seam, got the outburst dangerous grade samples of the outburst mines. Based on it, programmed the neural network and trained it. Put the trained neural network, the indexes database of coal and gas outburst and other programs together constituted the system to evaluate the mine outburst dangerous grade. And applied it to a few outburst mines engineering verification of Huainan diggings.The research of this text for the demarcation method of outburst mines dangerous grade of out country outburst mines has the certain guidance meaning for establish our country demarcation method and evaluation standard of outburst mines dangerous degree.