Applying data mining techniques to explore factors contributing to occupational injuries in Taiwan's construction industry

Ching Wu Cheng, Sou Sen Leu, Ying Mei Cheng, Tsung Chih Wu, Chen Chung Lin

研究成果: Article同行評審

65 引文 斯高帕斯(Scopus)

摘要

Construction accident research involves the systematic sorting, classification, and encoding of comprehensive databases of injuries and fatalities. The present study explores the causes and distribution of occupational accidents in the Taiwan construction industry by analyzing such a database using the data mining method known as classification and regression tree (CART). Utilizing a database of 1542 accident cases during the period 2000-2009, the study seeks to establish potential cause-and-effect relationships regarding serious occupational accidents in the industry. The results of this study show that the occurrence rules for falls and collapses in both public and private project construction industries serve as key factors to predict the occurrence of occupational injuries. The results of the study provide a framework for improving the safety practices and training programs that are essential to protecting construction workers from occasional or unexpected accidents.

原文English
頁(從 - 到)214-222
頁數9
期刊Accident Analysis and Prevention
48
DOIs
出版狀態Published - 2012 九月 1

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health

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