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

  • 2023
  • OriginalPaper
  • Chapter
Published in:
Authors
Dan Chang
Min Zhang
Daqing Gong
Published in
IEIS 2022
Publisher
Springer Nature Singapore

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Abstract

The chapter explores the application of text mining and complex network theory to identify and evaluate key factors contributing to railway accidents. By analyzing accident reports from China and the UK, the study constructs an importance evaluation model that considers both word frequency and the correlation between factors. The model is validated through comparisons with traditional methods, demonstrating its effectiveness in enhancing railway safety management. The study concludes that human and management factors are critical in reducing accident risks, highlighting the need for improved training and stricter safety measures.
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previous chapter Research on Copyright Protection of Digital Publications Based on Blockchain Technology
next chapter The Contradiction Between Private Tutoring Industry and Capitalization
Title
Importance Evaluation of Factors for the Railway Accidents Based on TF-K
Authors
Dan Chang
Min Zhang
Daqing Gong
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
IEIS 2022

Print ISBN: 978-981-9936-17-5

Electronic ISBN: 978-981-9936-18-2

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-99-3618-2_7
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