Safety risk identification method of fully mechanized mining surface based on fuzzy neural network

Due to the complex and changeable working environment of fully mechanized mining surface, the traditional safety risk identification method is difficult to reflect the actual situation, and the safety risk identification method of fully mechanized mining surface based on fuzzy neural network is proposed. Collect and preprocess the safety risk factor data of fully mechanized coal mine, construct a fuzzy neural network model, input the preprocessed data, and output the identification results of the safety risk level of fully mechanized coal mine. The experimental results show that the correct rate of the result is 97.22% and the identification accuracy is high.