[关键词]
[摘要]
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。
[Key word]
[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.
[中图分类号]
[基金项目]
国家自然科学基金(71071173);重庆市科技攻关项目(2010GGB108);教育部高等学校博士学科点科研基金(20090191110004);中央高校基本科研业务费科研专项自然科学类面上项目(CDJZR10110012)