Coal Mine Safety Evaluation System

The coal industry is the foundation of China’s national economy and plays a crucial role in the development of the national economy.However,with the deepening of the situation in China’s coal mines and the changes in China’s environment,the level of coal mine safety has not changed along with the economy.The rapid development of development and the current status of coal mine safety are not optimistic.Therefore,the establishment of a safety assessment model system plays a crucial role in the safety management of coal mines in China.After fully understanding the characteristics of coal mine safety production,according to the risk assessment index system research,five types of risk factors for evaluation were established,mainly human factors,equipment factors,management factors,environmental factors and information factors.After continuous analysis and comparison,Because of its unique advantages,the neural network evaluation system can be fully developed in the evaluation system.The neural network,self-organization,learning,and highly nonlinear characteristics make the neural network used for safety evaluation model more adequate.Guaranteed and highly enforceable.In the system that builds the neural network model,the BP artificial neural network is selected and the system is built.The number of hidden layers and hidden layer nodes of the BP artificial neural network is established.The BP neural network is used for programming with the matlab software.The network’s additional weight algorithm and elastic algorithm are used to evaluate the safety system of the entire coal mine.The results show that the selected training method can complete the evaluation task in a short period of time and meet the standards of the coal mine safety evaluation system.Therefore,using the artificial neural network to study the coal mine safety and evaluation system is operability,and the evaluation result is relatively accurate,which can effectively analyze the coal mine safety work and make a certain theoretical research for the future research and development.