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Importance Evaluation of Factors for the Railway Accidents Based on TF-K

In: Ieis 2022

Author

Listed:
  • Dan Chang

    (Beijing Jiaotong University)

  • Min Zhang

    (Beijing Jiaotong University)

  • Daqing Gong

    (Beijing Jiaotong University)

Abstract

Rail accidents cause casualty and financial loss to society. In order to extract and identify the key factors from the accident reports more accurately, this study added the word frequency-correlation importance evaluation function(TF-K*) based on complex network on the basis of text mining, and built an importance evaluation model of factors for the railway accidents. When evaluating the importance of factors, the word frequency and the correlation between factors can be considered simultaneously. In this study, 213 railway accident reports from China and Britain were collected to analyze the cause of the accident, and the final results also verified the validity of the model.

Suggested Citation

  • Dan Chang & Min Zhang & Daqing Gong, 2023. "Importance Evaluation of Factors for the Railway Accidents Based on TF-K," Lecture Notes in Operations Research, in: Menggang Li & Guowei Hua & Xiaowen Fu & Anqiang Huang & Dan Chang (ed.), Ieis 2022, pages 63-76, Springer.
    • Handle: RePEc:spr:lnopch:978-981-99-3618-2_7
    DOI: 10.1007/978-981-99-3618-2_7
    as

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