English  |  正體中文  |  简体中文  |  Items with full text/Total items : 6480/11652
Visitors : 20218687      Online Users : 99
RC Version 3.2 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search
LoginUploadHelpAboutAdminister

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/16663

Title: Applying Data Mining Techniques to Explore Factors Contributing to Occupational Injuries in Taiwan’s Construction Industry
Authors: Cheng, Ching-Wu;Leu, Sou-Sen;Cheng, Ying-Mei;Wu, Tsung-Chih;Lin, Chen-Chung
Contributors: 工業教育與技術學系
Keywords: Construction industry;Occupational accidents;Data mining;Safety management;Data analysis
Date: 2012-09
Issue Date: 2013-06-05T07:24:22Z
Publisher: Elsevier
Abstract: 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.
Relation: Accident Analysis and Prevention, 48: 214-222
Appears in Collections:[工業教育與技術學系] 期刊論文

Files in This Item:

File SizeFormat
index.html0KbHTML473View/Open


All items in NCUEIR are protected by copyright, with all rights reserved.

 


DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback