Bayes stepwise discriminant analysis model and application of coal and gas outburst prediction

Bayes stepwise discriminant model is established to predict the coal and gas outbursts accurately and reliably based on the principle of discriminant analysis theory.Three sensitive indexes of coal and gas outburst such as initial speed of methane diffusion, gas pressure and soft layer thickness are regarded as the discriminant factors of the Bayes discriminant analysis model by stepwise discriminant analysis method.Meanwhile, the risk of coal and gas outburst is divided into four levels as the four normal states of Bayes discriminant analysis.The discriminant function are obtained through training of twenty sets of coal and gas outburst data by using the constructed discriminant model.Each of the twenty sets of samples is tested by using resubstitution method according to the Bayes discriminant method, and the misjudgment rate is equal to zero.The established discriminant model is applied to eight sets of coal and gas outburst examples for discriminant prediction, and the results are in perfect agreement with the actual situation.