摘要
针对定性的安全评价与分析逐渐不能满足个人对安全要求的现状,为了更好地量化描述生活中的风险程度,找到异常值与个体风险之间的量化关系,利用逻辑回归方法分析各个自变量和因变量之间的具体依赖关系;以河南某水泥厂为调查对象,建立基于逻辑回归方法的应急预警模式,利用SAS软件对自变量与事故后果之间的线性关系进行计算分析,并与聚类分析方法进行了比较。结果表明:逻辑回归模型相较于聚类分析对于异常值的监测有较好的精度,为个人风险预警及事故预防提供了很好的分析基础。
Qualitative safety evaluation and analysis can not meet individual safety requirements gradually. In order to better quantify the degree of risk in life and find the quantitative relationship between outliers and individual risk,this paper uses logical regression method to analyze the specific dependencies between independent variables and dependent variables. Taking a cement plant in Henan Province as the investigation object,an emergency early warning model based on logistic regression method is established. The linear relationship between independent variables and accident consequences is calculated and analyzed by SAS software,and compared with cluster analysis method. The results show that compared with clustering analysis,logistic regression model has better accuracy in monitoring outliers,which provides a good analysis basis for individual risk warning and accident prevention.
作者
杨鑫刚
马遥
王起全
YANG Xingang;MA Yao;WANG Qiquan(School of Labor Education,China University of Labor Relations,Beijing 100048,China;School of Safety Engineering and Emergency Management,Shijiazhuang Tiedao University,Shijiazhuang 050043,China;College of Safety Engineering,China University of Labor Relations,Beijing 100048,China)
出处
《自然灾害学报》
CSCD
北大核心
2022年第6期50-55,共6页
Journal of Natural Disasters
基金
教育部2021年第一批产学合作协同育人项目(202101313004)
中国劳动关系学院“中央高校基本业务费专项资金”项目(22ZYJS011)。
关键词
逻辑回归
应急预警
机器学习
异常值
个体风险
logistic regression
emergency warning
machine learning
outliers
individual risk
