Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
A Guide To The Project Management Body Of Knowledge (PMBOK Guides)
A Guide To The Project Management Body Of Knowledge (PMBOK Guides)
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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.