Paper Title:
Building the CBR-Based Identification System Framework for Construction Accident Precursors
  Abstract

Construction accident precursors(CAPs) are potential upcoming accident signals and offer the possibility for improving safety management performance. Case-based reasoning (CBR) as an artificial intelligence(AI) tools can be used to improve the efficiency and quality of CAPs identification. This paper developed a system framework for identifying CAPs on construction sites using CBR. There were ten indicators, including six problem indicators and four solution indicators were identified to describe the CAPs case between the accident characteristics and corresponding precursors. Especially, a technique case-based adaptation was implemented in the adaptation stage of CBR called inner CBR and three indicators were identified to describe the adaptation case. Eventually, the CAPs identification system framework was presented and a case study based on actual accident case from US Department of OSHA was used to illustrate how to seek CAPs.This research provides a new way to acquire more useful information from historical accident records in order to improve safety on construction sites for future ongoing project.

  Info
Periodical
Advanced Materials Research (Volumes 255-260)
Edited by
Jingying Zhao
Pages
546-550
DOI
10.4028/www.scientific.net/AMR.255-260.546
Citation
X. Z. Liu, T. S. Zhao, K. Xiao, "Building the CBR-Based Identification System Framework for Construction Accident Precursors", Advanced Materials Research, Vols. 255-260, pp. 546-550, 2011
Online since
May 2011
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Price
$32.00
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