China Safety Science Journal ›› 2022, Vol. 32 ›› Issue (6): 103-108.doi: 10.16265/j.cnki.issn1003-3033.2022.06.2262

• Safety engineering technology • Previous Articles     Next Articles

Research on text classification of railway safety incidents based on BLS

SHANG Linyu1(), YIN Ming2, XIAO Chang3, CHENG Jun1   

  1. 1 Signal & Communication Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China
    2 CHN Energy Shuohuang Railway Development Co., Ltd.,Cangzhou Hebei 062350, China
    3 China Railway Society, Beijing 100844, China
  • Received:2022-01-12 Revised:2022-04-13 Online:2022-06-28 Published:2022-12-28

Abstract:

In order to prevent railway safety incidents, text mining related technologies and BLS were utilized to study effective incident classification mechanism, including four categories of equipment, construction, operation and external environmental problems. 314 pieces of text data were cleaned and structured, and Chinese word segmentation was built based on Jieba word segmentation + custom thesaurus+ custom stop word list. Then, 223 feature words were constructed based on Chi square test, and their weights were calculated based on TF-IDF. Finally, accident causes were classified according to BLS, and three classification methods were designed. The results show that the system can form an effective classification model through mining text information of railway safety event reports. And it can save computing power by utilizing features of BLS, and improve classification accuracy by adding feature enhancement nodes, so as improve industry management level.

Key words: broad learning system (BLS), railway safety incident, text classification, term frequency-inverse document frequency (TF-IDF), text mining