Safety evaluation of hazards based on discrete Hopfield neural network
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Abstract:
In order to evaluate hazard’s level efficiently and decrease disasters’ influence on the surrounding environment，a safety evaluation index system of hazards is set up first by considering influence factors of personnel，equipment，raw material，technology，and environment. Then，a hazards safety evaluation model is built by combining neural network with safety system engineering theory. Finally，case studies testify the model can evaluate the hazards’ level reasonably and objectively.
