重庆科技大学学报（自然科学版）2024，Vol.26Issue(6)：80-87,8.DOI:10.19406/j.issn.2097-4531.2024.06.012
基于Apriori算法和贝叶斯网络的高处坠落事故致因分析
Analysis of Falling Accident Causes Based on Apriori Algorithm and Bayesian Network
摘要
Abstract
The accident cause analysis based on association rule algorithm and Bayesian network is carried out to address the falling accident hazards in building construction.Firstly,131 reports of falling accidents in building construction from the year 2018-2022 are statistically analyzed,from which 24 factors leading to accidents were ex-tracted.Secondly,Apriori algorithm is used to explore the strong association rules among these factors to suggest their intrinsic connections,and a Bayesian network model of falling accidents is constructed by combining expert experience.Then,the high-frequency factors are identified based on the statistical frequency analysis data,while the critical paths and high sensitivity factors of accidents are identified with the help of Genie software for backward inference and sensitivity analysis of this Bayesian network.关键词
Apriori算法/贝叶斯网络/事故致因/高处坠落事故Key words
Apriori algorithm/Bayesian network/accident causes/falling accidents分类
建筑与水利引用本文复制引用
田晓敏,李晓冬..基于Apriori算法和贝叶斯网络的高处坠落事故致因分析[J].重庆科技大学学报（自然科学版）,2024,26(6):80-87,8.基金项目
住房和城乡建设部科技计划软科学项目"工程保险与住建领域信用信息管理耦合机制研究"(2022-R-048) （2022-R-048）
