Study on the electromagnetic radiation predicting method of coal and gas outburst based on self-adapting neural network

Artificial neural network can determine a non-linear reflecting relation of input and output variables by learning and training. According to the reflecting relation, it can realize a dynamic predicting of monitoring data. Therefore, the principle of electromagnetic radiation (EMR) self-adapting neural network predicting coal and gas outburst is studied on the basis of the basic principle of artificial neural network, and applied to predicting the criticality of coal and gas outburst. It realizes an EMR dynamic trend prediction of the criticality of coal and gas outburst. The application results show that the EMR neural network predicting method of coal and gas outburst has many characteristics of simple predicting method, save time and labour, high accuracy, and so on. It is feasible to be applied to predicting the criticality of coal and gas outburst.