Introduced the theory of three types of hazardous sources, and it recognized and analysed such three types of hazardous sources as the factor of inherent hazardous source, factor of inducing hazardous source and facto...Introduced the theory of three types of hazardous sources, and it recognized and analysed such three types of hazardous sources as the factor of inherent hazardous source, factor of inducing hazardous source and factor of men, which affect the safety and reliability of coal-dust explosion risk system and then builds up the risk factor indices of coal-dust explosion according to analysis of conditions inducing the coal-dust explosion. It fixes the risk degree of coal-dust explosion risk system by analyzing loss probability and loss scope of risk system and by means of the probabilistic hazard evaluation method and risk matrix method, etc.. According to the feature of strong capability of nonlinear approximation of BP neural network, the paper designed the structure of BP neural network for the risk evaluation of the mine coal-dust explosion with BP neural network. And the weight of the network was finally determined by training the given samples so that the risk degree of samples to be measured could be exactly evaluated and the risk of mine coal-dust explosion could be alarmed in good time.展开更多
文摘Introduced the theory of three types of hazardous sources, and it recognized and analysed such three types of hazardous sources as the factor of inherent hazardous source, factor of inducing hazardous source and factor of men, which affect the safety and reliability of coal-dust explosion risk system and then builds up the risk factor indices of coal-dust explosion according to analysis of conditions inducing the coal-dust explosion. It fixes the risk degree of coal-dust explosion risk system by analyzing loss probability and loss scope of risk system and by means of the probabilistic hazard evaluation method and risk matrix method, etc.. According to the feature of strong capability of nonlinear approximation of BP neural network, the paper designed the structure of BP neural network for the risk evaluation of the mine coal-dust explosion with BP neural network. And the weight of the network was finally determined by training the given samples so that the risk degree of samples to be measured could be exactly evaluated and the risk of mine coal-dust explosion could be alarmed in good time.
