Risk factor analysis is a key research topic in the field of computer science.Due to the complexity of risk factors and the tendency of search algorithms to become trapped in local optima,this paper proposes a grey wolf sensing optimization algo-rithm(GWSOA).This algorithm employs a grey wolf optimization algorithm with sensing and mutation capabilities to filter the ini-tial set of risk factors,aiming to determine the final set of risk factors.Experiments conducted on 12 datasets demonstrate that GWSOA achieves the best average fitness values on 11 of these datasets,outperforming all baseline methods.
关键词
危险因素分析/搜索算法/灰狼感知优化算法
Key words
risk factor analysis/search algorithm/grey wolf sensing optimization algorithm
万方数据