• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.138-147
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• 2006

The objective of this research is to explore a more precise forecasting method by applying Case-based Reasoning (CBR). The newly suggested method in this study enables project managers to forecast monthly expenditures with less time and effort by retrieving and referring only projects of a similar nature, while filtering out irrelevant cases included in database. For the purpose of accurate forecasting, 1) the choice of the numbers of referring projects and 2) the better selection among three levels ? which include a 20-work package level, a 7-major work package level, and a total sum level analysis, were investigated in detail. It is concluded that selecting similar projects at $12{\sim}19%$ out of the whole database will produce a more precise forecasting. The new forecasting model, which suggests the predicted values based on previous projects, is more than just a forecasting methodology; it provides a bridge that enables current data collection techniques to be used within the context of the accumulated information. This will eventually help all the participants in the construction industry to build up the knowledge derived from invaluable experience.