摘要
为充分发挥安全生产责任保险(安责险)在促进安全生产方面的积极作用,提出了基于风险评估的非煤矿山尾矿库安责险保费计算方法。利用层次分析法和熵权法确定组合权重,构建了包含"人、物、环境、管理和项目特性"等内容的尾矿库安全风险模糊综合评估体系。基于湖南省58个尾矿库承保样本数据,采用AGA-RBF神经网络模型建立各尾矿库实际安全风险状况与安责险调节系数之间的关系,以确定企业安全风险修正系数,从而修正基本保费,实现不同企业的差别费率。研究结果可为保险机构评估矿山企业安全风险和确定合适的安责险保费提供参考,助力我国矿山企业安责险的推广实施。
In order to give full play to safety liability insurance to play apositive role in promoting work safety,a calculation method of safety liability insurance for non-coal mine tailings pond based on risk assessment was proposed.By using AHP and entropy weight method to determine the combined weight,a fuzzy comprehensive assessment system of safety risk of tailing pond was established,which included"human,material,environment,management and project characteristics".Based on the underwriting sample data of 58 tailings ponds in Hunan province,the relationship between the actual safety risk status of each tailings pond and the adjustment coefficient of safety liability insurance was established by the AGA-RBF neural network model,so as to determine the safety risk correction coefficient of the enterprise,further to correct the basic insurance and to achieve the different cost rates of different enterprises.The research results can provide a reference for insurance institutions to assess the safety risk of enterprises and to make appropriate insurance,promoting the implementation of safety liability insurance in China\s mines.
作者
仇一颗
黄洁
刘晓明
QIU Yike;HUANG Jie;LIU Xiaoming(College of Civil Engineering,Hunan University,Changsha,Hunan 410082,China)
出处
《矿业研究与开发》
CAS
北大核心
2020年第7期167-172,共6页
Mining Research and Development
基金
国家自然科学基金项目(51578230)。
关键词
非煤矿山尾矿库
安全生产责任保险
风险评估
模糊综合评价法
RBF神经网络
Non-coal mine tailings pond
Liability insurance of work safety
Risk assessment
Fuzzy comprehensive evaluation method
RBF(Radical basis function)neural network
