TY - JOUR
T1 - Development of project cost contingency estimation model using risk analysis and fuzzy expert system
AU - Idrus, Arazi
AU - Fadhil Nuruddin, Muhd
AU - Rohman, M. Arif
PY - 2011/3
Y1 - 2011/3
N2 - Contractors traditionally estimate cost contingency based on subjective judgment, such as 5-10% from the cost estimated by considering past similar project. However, such method does not have a sound basis and is difficult to justify or defend. Therefore, more objective methods for estimating project cost contingency have been presented. However, most of the methods still rely on formal modeling techniques, which is not easy to be applied in construction industry. This research proposes a method to estimate cost contingency using a flexible and rational approach that could accommodate contractors' subjective judgment based on risk analysis and fuzzy expert system concept. In this research, the proposed method involved the development of cost contingency model for building and infrastructure projects in Malaysia. According to the validation result, it was found that the predictions given by the system were within 20% accuracy compared to actual cost contingencies.
AB - Contractors traditionally estimate cost contingency based on subjective judgment, such as 5-10% from the cost estimated by considering past similar project. However, such method does not have a sound basis and is difficult to justify or defend. Therefore, more objective methods for estimating project cost contingency have been presented. However, most of the methods still rely on formal modeling techniques, which is not easy to be applied in construction industry. This research proposes a method to estimate cost contingency using a flexible and rational approach that could accommodate contractors' subjective judgment based on risk analysis and fuzzy expert system concept. In this research, the proposed method involved the development of cost contingency model for building and infrastructure projects in Malaysia. According to the validation result, it was found that the predictions given by the system were within 20% accuracy compared to actual cost contingencies.
KW - Construction project
KW - Cost contingency
KW - Fuzzy expert systems
KW - Risk analysis
UR - http://www.scopus.com/inward/record.url?scp=78049531038&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2010.07.061
DO - 10.1016/j.eswa.2010.07.061
M3 - Article
AN - SCOPUS:78049531038
SN - 0957-4174
VL - 38
SP - 1501
EP - 1508
JO - Expert Systems with Applications
JF - Expert Systems with Applications
IS - 3
ER -