集美大学学报（自然科学版）2024，Vol.29Issue(1)：32-38,7.DOI:10.19715/j.jmuzr.2024.01.05
基于物元可拓和神经网络的危化品港口危险等级评价模型
Evaluation Model on Hazard Categories in Dangerous Chemical Port Based on Object Topology and BP Neural Network
刘翠莲 1王杰1
作者信息
- 1. 大连海事大学交通运输工程学院,辽宁 大连 116000
- 折叠
摘要
Abstract
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.关键词
港口危险等级评价/物理-事理-人理/BP神经网络/G1法/物元可拓理论Key words
port hazard category evaluation/Wuli-Sshili-Renli(WSR)/BP neural network/G1 method/matter-element extension theory分类
交通工程引用本文复制引用
刘翠莲,王杰..基于物元可拓和神经网络的危化品港口危险等级评价模型[J].集美大学学报（自然科学版）,2024,29(1):32-38,7.
