Evaluation Model on Hazard Categories in Dangerous Chemical Port Based on Object Topology and BP Neural Network
In order to accurately and quickly detemine the hazard categories in dangerous chemical ports and reduce the chance of risky accidents in ports,an evaluation model for fast classification is proposed.Ac-cording to the WSR methodology,the evaluation system of port hazard level is constructed,and the sectional and classical domains of each hazard level are determined by establishing the material element extension theory model,and the hazard levels of ten major domestic dangerous chemical ports in 2018 and 2020 are derived and used as data samples,which are randomly divided into training and testing sets for BP neural network training.The results show that the selected indicators can comprehensively reflect the hazard levels of the ports,and the evaluation model results after the neural network training are largely consistent with the actual levels.The mod-el can be used to quickly evaluate the hazard level of a port,which can better avoid random errors brought by human factors.
port hazard category evaluationWuli-Sshili-Renli(WSR)BP neural networkG1 methodmatter-element extension theory
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