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The importance of cost estimating is well recognized as it predicts the costs of construction and provides a basis for the contractor to submit a bid for a project. As each project is unique and no two are quite a like, subjective judgments are needed to adjust the estimating norms, which are based on historical data and experience of estimators to suit the proposed site conditions. Hence, the estimating practice has large element of subjective process rather than a precise technical and analytical process. The direct cost is established with two types of data namely factual and productivity Factual data are fixed and can be determined with certainty. However, productivity data are not permanently fixed and need subjective judgments of estimators in determination. The established average norms of direct cost elements such as labour, equipment and material have to be adjusted to suit each project conditions. This study aimed at developing a fuzzy expert model, which produces a deterministic output for productivity multiplier to adjust the standard rates. As a mode of approach factors, which include activity characteristics and project conditions, influencing resource usage are identified. Further, relationships among the factors and resource usage are quantified using generalized expert knowledge and an artificial intelligence technique called fuzzy logic. The use of fuzzy expert system removes the subjective questionable human factors as much as possible by providing a base with objective data and improves the efficiency of the estimating practice. Keywords: Fuzzy Logic, Cost Estimating, Standard Norms, Activity Characteristics and Project Conditions |
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