机械与电子2025，Vol.43Issue(11)：22-27,6.
基于隐马尔可夫模型的事故安全风险态势感知模型
Accident Safety Risk Situation Awareness Model Based on Hidden Markov Models
摘要
Abstract
To address the frequent safety incidents in high-risk manufacturing enterprises that threat-en both production operations and social stability,this study proposes a safety risk situation awareness ap-proach based on historical accident data and the integration of a hidden Markov model(HMM).The meth-od characterizes potential risk states and their transition patterns,and employs an improved Viterbi algo-rithm to infer the most probable risk evolution path,thereby enabling dynamic prediction of risk trends.Experimental results demonstrate that the proposed method can accurately reveal the characteristics of risk state changes and significantly improve the accuracy of risk identification and prediction.The findings pro-vide new perspectives and technical support for the development of risk monitoring and early warning sys-tems.关键词
隐马尔可夫模型/安全风险态势感知/维特比算法/风险预测Key words
hidden Markov model/safety risk situation awareness/Viterbi algorithm/risk prediction分类
数理科学引用本文复制引用
杨赟,汤卫..基于隐马尔可夫模型的事故安全风险态势感知模型[J].机械与电子,2025,43(11):22-27,6.基金项目
2023年度贵州开放大学(贵州职业技术学院)科学研究项目(2023YB26) （贵州职业技术学院）
