%0 Journal Article %T 危险源安全评价的离散Hopfield神经网络 %T Safety evaluation of hazards based on discrete Hopfield neural network %A 刘胜 %A 刘娜 %A 杨育 %A 贾建国 %A LIU,Sheng %A LIU,Na %A YANG,Yu %A JIA,Jianguo %J 重庆大学学报 %J Journal of Chongqing University %@ 1000-582X %V 36 %N 4 %D 2013 %P 26-32 %K 神经网络;危险源;评价模型 %K neural networks;hazards;evaluation model %X 为了快速有效地评价危险源等级,及时响应危险事故给周边人口及环境带来的危害,在考虑引发危险事故人员、设备、原料、技术、环境因素基础上,构建了系统的危险源安全评价指标体系。结合离散Hopfield神经网络结构特点及原理,建立了基于离散Hopfield神经网络的危险源安全评价模型,并通过实例验证该模型,合理客观地对危险源进行评价分级。 %X 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. %R 10.11835/j.issn.1000-582X.2013.04.004 %U http://qks.cqu.edu.cn/cqdxzrcn/home %1 JIS Version 3.0.0