Highlights Logistics-DT-TFP is proposed for analyzing the causes of RDGT accidents. Ordered multi-classification Logistic regression is used to analyze cause and accident severity. SMOTE-Tomek mixed sampling is used for data balance. DT and C5.0 algorithm are used to extract and analyze the coupling rules. TOP-K Improved FP-Growth is used to mine association and supplement coupling rules.

    Abstract Accurately and quickly mining the hidden information in railway dangerous goods transportation (RDGT) accident reports has great significance for its safety management. In this paper, a data mining method Logistics-DT-TFP is proposed for analysing the causes of RDGT accidents. Firstly, analyse the transportation process, extract the cause of the accident, and classify the severity of the accident. Then, using ordered multi-classification Logistic regression for correlation calculation, qualitatively judge and quantitatively analyse the relationship between each cause and the severity of the accident. The feature tags of the Decision Tree (DT) are screened, the C5.0 algorithm is used to obtain the accident coupling rules. Next, the FP-Growth algorithm is used to mine frequent itemsets, and TOP-K is used to improve it and output effective association rules with the degree of lift as the indicator, which avoids repeated traversal of the database, shortens the time complexity, and reduces the impact of the minimum support setting on the calculation results. The degree of lift among the causes in the coupling chain is calculated as a complement to the extraction of coupling rules. Finally, based on the analysis and mining results of case study, the management strategies for railway dangerous goods are proposed.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Mining the accident causes of railway dangerous goods transportation: A Logistics-DT-TFP based approach


    Contributors:
    Fa, Huiyan (author) / Shuai, Bin (author) / Yang, Zhenlong (author) / Niu, Yifan (author) / Huang, Wencheng (author)


    Publication date :

    2023-12-02




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Safety evaluation of railway dangerous goods transportation

    Zheng, Manzhi / Zhao, Changming / Liang, Tongtian et al. | British Library Conference Proceedings | 2022


    Safety evaluation of railway dangerous goods transportation

    Zheng, Manzhi / Zhao, Changming / Liang, Tongtian et al. | SPIE | 2022


    Dangerous goods transportation logistics vehicle with protection device

    HU XIAOYAN / GONG JINHUI | European Patent Office | 2021

    Free access

    Railway transportation of dangerous goods: a bibliometric aspect

    Kolesnykova Tetiana / Matveyeva Olena / Manashkin Lev et al. | DOAJ | 2019

    Free access

    Dangerous goods transportation carriage and dangerous goods transportation vehicle

    WANG GUOFENG | European Patent Office | 2021

    Free access