The Mine Emergency Management Capability Based on EWM-CNN Comprehensive Evaluation

Abstract

By establishing an evaluation system for emergency management capability for coal mine enterprises, the problems and shortfalls in coal mine emergency management can be identified. Moreover, this evaluation method holds promise in enhancing the ability to respond to emergencies in coal mines. The current research conducts both theoretical analysis and field research to determine and extract 26 factors that impact the emergency management capability of coal mining companies. The collected data is analyzed using SPSS version 24.0 and undergoes reliability and validity assessments. Subsequently, the entropy weight technique is utilized to determine the weight of individual evaluation system indices. As an effective evaluation tool, the trained convolutional neural network (CNN) model can accurately and effectively predict the satisfaction of the samples outside the training sample set, providing suggestions for improving coal mine emergency management. The trained model is employed to make empirical predictions and analyze the XY coal mine. The findings indicate that the overall emergency management capacity of the coal mine is II, which is at a good level. The evaluation results are consistent with the actual situation, and suggestions are provided for improving the emergency management ability of coal mines.