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A platform for research: civil engineering, architecture and urbanism
Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning
AbstractAdequate estimation of construction costs is a key factor in construction projects. This paper examines the performance of three cost estimation models. The examinations are based on multiple regression analysis (MRA), neural networks (NNs), and case-based reasoning (CBR) of the data of 530 historical costs. Although the best NN estimating model gave more accurate estimating results than either the MRA or the CBR estimating models, the CBR estimating model performed better than the NN estimating model with respect to long-term use, available information from result, and time versus accuracy tradeoffs.
Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning
AbstractAdequate estimation of construction costs is a key factor in construction projects. This paper examines the performance of three cost estimation models. The examinations are based on multiple regression analysis (MRA), neural networks (NNs), and case-based reasoning (CBR) of the data of 530 historical costs. Although the best NN estimating model gave more accurate estimating results than either the MRA or the CBR estimating models, the CBR estimating model performed better than the NN estimating model with respect to long-term use, available information from result, and time versus accuracy tradeoffs.
Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning
Kim, Gwang-Hee (author) / An, Sung-Hoon (author) / Kang, Kyung-In (author)
Building and Environment ; 39 ; 1235-1242
2004-02-17
8 pages
Article (Journal)
Electronic Resource
English
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