摘要
作为避免桥梁安全事故和确保公众安全的一种重要途径,桥梁风险评估得到了国内外学者的广泛关注.然而,现有的桥梁风险评估模型大多忽视了在建模过程中优化与模型相关的参数取值和参数数量,导致无法有效提升桥梁风险评估的准确性.为此,本文在现有基于扩展置信规则库的桥梁风险评估模型的基础上,通过引入参数优化和数据包络分析分别提出扩展置信规则库的规则生成方法和规则约减方法,再以此进一步提出扩展置信规则库的联合优化方法,确保应用于桥梁风险评估模型中的扩展置信规则库具有最优的参数取值和参数数量.文末,引入桥梁风险评估领域中常用的公认数据集验证所提模型的有效性.通过与已有研究成果相对比,结果表明基于扩展置信规则库联合优化的桥梁风险评估模型在提高评估准确性和降低模型复杂度方面均有良好表现.
As an important approach to avoiding the safety accidents of bridges and ensuring the safety of the public,bridge risk assessments have been widely concerned by lots of scholars.However,the existing models of bridge risk assessment mostly ignored the optimization of the value of parameters and the number of parameters in modeling process,leading to the failure of improving the accuracy of bridge risk assessment.Therefore,based on the existing bridge risk assessment model using extended belief rule base(EBRB),this paper proposes a rule generation method and a rule reduction method based on parameter optimization and data envelopment analysis,then a joint optimization methods is further proposed for optimizing EBRB.Finally,a commonly used and well-known dataset about bridge risk assessment is applied to validate the efficiency of the proposed model.In comparison with the results of previous studies,the bridge risk assessment model based on EBRB with joint optimization has shown superior performance in both improving the evaluation accuracy and reducing the modeling complexity.
作者
杨隆浩
叶菲菲
王应明
YANG Longhao;YE Feifei;WANG Yingming(Decision Sciences Institute,Fuzhou University,Fuzhou 350116,China;Key Laboratory of Spatial Data Mining&Information Sharing of Ministry of Education,Fuzhou University,Fuzhou 350116,China)
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2020年第7期1870-1881,共12页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(61773123,71701050)
教育部人文社科项目(20YJC630188)
福建省社会科学规划项目(FJ2019C032)。
关键词
桥梁风险评估
扩展置信规则库
联合优化
参数数量
参数取值
bridge risk assessment
extended belief rule base
joint optimization
number of parameters value of parameters
