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[1]白金花,刘勇,程智慧,等.基于ARMA-SSESM组合模型的危险品道路运输泄漏事故预测研究*[J].中国安全生产科学技术,2023,19(10):171-177.[doi:10.11731/j.issn.1673-193x.2023.10.024]
　BAI Jinhua,LIU Yong,CHENG Zhihui,et al.Research on prediction of hazardous materials road transportation leakage accident based on ARMA-SSESM combination model[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(10):171-177.[doi:10.11731/j.issn.1673-193x.2023.10.024]
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基于ARMA-SSESM组合模型的危险品道路运输泄漏事故预测研究*()
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
19
期数:
2023年10期
页码:
171-177
栏目:
职业安全卫生管理与技术
出版日期:
2023-10-31

文章信息/Info

Title:
Research on prediction of hazardous materials road transportation leakage accident based on ARMA-SSESM combination model
文章编号:
1673-193X(2023)-10-0171-07
作者:
白金花; 刘勇; 程智慧; 向前前; 施星宇
（1.湖南科技大学 资源环境与安全工程学院，湖南 湘潭 411201；
2.湖南科技大学 煤矿安全开采技术湖南省重点实验室，湖南 湘潭 411201；
3.湖南科技大学 南方煤矿瓦斯与顶板灾害预防控制安全生产重点实验室，湖南 湘潭 411201；
4.长沙理工大学 电气与信息工程学院，湖南 长沙 410114)
Author(s):
BAI Jinhua;  LIU Yong;  CHENG Zhihui;  XIANG Qianqian;  SHI Xingyu
(1.College of Resources Environment and Safety Engineering,Hunan University of Science and Technology;
2.Hunan Provincial Key Laboratory of Safe Mining Techniques of Coal Mines,Hunan University of Science and Technology;
3.Work Safety Key Lab on Prevention and Control of Gas and Roof Disasters for Southern Coal Mines,Hunan University of Science and Technology;
4.School of Electrical & Information Engineering,Changsha University of Science & Technology)
关键词:
危险品; 道路运输; ARMA模型; SSESM模型; 组合预测模型; 事故预测
Keywords:
hazardous materials;  road transportation;  autoregressive moving average (ARMA) model;  simple seasonal exponential smoothing method (SSESM) model;  combined prediction model;  accident prediction
分类号:
X951
DOI:
10.11731/j.issn.1673-193x.2023.10.024
文献标志码:
A
摘要:
为了预测危险品道路运输泄漏事故数量，以2013—2020年危险品道路运输泄漏月度事故为基础，运用时间序列理论建立自回归滑动平均（ARMA）预测模型和简单季节指数平滑法(SSESM)预测模型以及组合预测模型，对2021年1月—2021年6月的危险品道路运输泄漏事故数量进行预测，并对3种模型的预测精度进行比较。研究结果表明：组合预测模型的预测精度最佳，能够有效拟合时间序列的整体趋势。研究结果可为危险品道路运输泄漏事故预防工作提供参考。
Abstract:
In order to predict the number of road transportation leakage accidents of hazardous materials,based on the monthly accidents of road transportation leakage of hazardous materials from 2013 to 2020,the autoregressive moving average (ARMA) prediction model,the simple seasonal exponential smoothing method (SSESM) prediction model and the combined prediction model are established by using time series theory.The number of road transport leakage accidents of dangerous chemicals from January to June 2021 is predicted,and the prediction accuracies of the three models are compared.The results show that the combined prediction model has the best prediction accuracy,and it can effectively fit the overall trend of the time series.The research results can provide reference for the prevention of leakage accidents in road transportation of hazardous materials.

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备注/Memo

备注/Memo:
收稿日期： 2023-05-11
* 基金项目： 国家自然科学基金项目（52074118）；湖南省教育厅科学研究项目（21A0306）；湖南省交通运输厅科技进步与创新计划项目（201943）
作者简介： 白金花，硕士研究生，主要研究方向为危险品道路运输风险评估。
通信作者： 刘勇，博士，副教授，主要研究方向为系统安全评价与预测、危险化学品运输安全、灾害预防与控制与火灾安全。
更新日期/Last Update: