根因分析研究综述  

Review of root cause analysis research

作　　者：程燕 王磊[1] 赵晓永 Cheng Yan;Wang Lei;Zhao Xiaoyong(Information Systems Institute,Beijing Information Science&Technology University,Beijing 100129,China;Beijing Advanced Innovation Center for Materials Genome Engineering,Beijing Information Science&Technology University,Beijing 100129,China)

机构地区：[1]北京信息科技大学信息系统研究所,北京100129 [2]北京信息科技大学北京材料基因工程高精尖创新中心,北京100129

出　　处：《计算机应用研究》2023年第4期961-966,共6页Application Research of Computers

基　　金：国家重点研发计划资助项目(2019YFB1705402);教育部人文社科规划基金资助项目(20YJAZH129);北京市教育委员会社科计划重点项目(SZ202011232024)。

摘　　要：作为问题发现和问题解决之间的关键问题与枢纽环节,根因分析目前的研究主要包括基于数据驱动和基于因果驱动两大类方法。鉴于数据驱动方法在缩小根因范围方面具有优势,因而目前根因研究主要聚焦在基于关联规则挖掘、基于启发式搜索、基于机器学习和基于深度学习等数据驱动方法,鲜有从因果知识的角度对根因进行分析,也尚未基于方法维度对根因进行归纳分析研究,缺乏相关研究成果。因此,对近几年根因分析的主要成果进行梳理总结,分析在不同方法维度下根因分析的区别及优势,并提出融合因果知识的根因分析方法,将非对称Shapley值与因果链图相结合以提升根因分析的准确度,最后讨论了现有的研究难点与发展趋势,提出有意义的未来研究方向。As a key problem and hub link between problem discovery and problem solving,the current research on root cause analysis mainly includes two types of methods:data-driven and causality-driven.In view of the advantages of data-driven methods in narrowing the range of root causes,at present,root cause research mainly focusses on data-driven methods such as association rule mining,heuristic search,machine learning and deep learning.There are few root cause analysis from the perspective of causal knowledge,nor has it been based on method dimension.The inductive analysis of the root cause is carried out,and there is a lack of relevant research results.Therefore,this paper sorted out and summarized the main results of root cause analysis in recent years,analysed the differences and advantages of root cause analysis under different method dimensions,and proposed a root cause analysis method that integrated causal knowledge,and combined asymmetric Shapley value with causal chain diagram to improve the accuracy of root cause analysis.Finally,the existing research difficulties and deve-lopment trends put forward meaningful future research directions.

关 键 词：根因分析 启发式算法 机器学习 深度学习 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]