Approach to analyze risk factors for construction projects utilizing fuzzy logic

Amiruddin Ismail, Abbas M. Abd, Zamri Bin Chik

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

To effectively manage the risks in construction projects, it is necessary for organizations to identify important risk and to provide a tool to measure their effects. This study is a part of a research aimed to provide a methodology for identifying and ranking risk sources and factors in construction projects as approach to create an integrated construction project management system. A common problem in project risk management processes is the need to determine the relative significance of different sources of risk in order to guide subsequent risk management effort and ensure it remains cost effective. A common approach is to rank risks in terms of probability and severity to identify sources of risk that will receive the most attention. In this study, the methodology used was the collection of data in the shape of previous researches and works, interviews with experts and questionnaire survey, followed by data analysis and interpretation using fuzzy logic. The main factors of risk around the integrated project management system was studied and determined in term of effect, probability of occurrence to weight each factor.

Original languageEnglish
Pages (from-to)3738-3742
Number of pages5
JournalJournal of Applied Sciences
Volume8
Issue number20
DOIs
Publication statusPublished - 2008

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Fuzzy logic
Project management
Risk management
Costs

Keywords

  • Construction project
  • Risks assessment
  • Utilizing fuzzy logic

ASJC Scopus subject areas

  • General

Cite this

Approach to analyze risk factors for construction projects utilizing fuzzy logic. / Ismail, Amiruddin; Abd, Abbas M.; Chik, Zamri Bin.

In: Journal of Applied Sciences, Vol. 8, No. 20, 2008, p. 3738-3742.

Research output: Contribution to journalArticle

Ismail, Amiruddin ; Abd, Abbas M. ; Chik, Zamri Bin. / Approach to analyze risk factors for construction projects utilizing fuzzy logic. In: Journal of Applied Sciences. 2008 ; Vol. 8, No. 20. pp. 3738-3742.
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