The attribute impact concept: Applications in case-based reasoning and parametric cost estimation
- Authors
- Ahn, Joseph; Ji, Sae-Hyun; Park, Moonseo; Lee, Hyun-Soo; Kim, Sooyoung; Suh, Sang-Wook
- Issue Date
- Jul-2014
- Publisher
- ELSEVIER SCIENCE BV
- Keywords
- Cost; Estimation; Attribute; Weight; Case-based reasoning; Regression analysis
- Citation
- AUTOMATION IN CONSTRUCTION, v.43, pp.195 - 203
- Journal Title
- AUTOMATION IN CONSTRUCTION
- Volume
- 43
- Start Page
- 195
- End Page
- 203
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/12516
- DOI
- 10.1016/j.autcon.2014.03.011
- ISSN
- 0926-5805
- Abstract
- The success of every construction project depends on the satisfactory achievement of a client's needs relating to cost, duration, and quality. Among them, costs must be managed with special awareness. In an effort to improve the estimate accuracy of cost during the initial stages of a building project, this research introduces the concept of 'attribute impact' (AI), which can measure the weights of attributes quantitatively and prioritize them. This study will also explain AI development, which adopts the impulse-momentum theorem of physics. For a case study, the project analyzes 163 public apartment buildings from 15 housing complex projects in Korea. To examine the validity of the proposed AI, the case study carries out two types of validation in terms of estimate accuracy using the parametric method and the case-based reasoning (CBR) applicability test. The validation results support the acceptable use of the suggested AI in measuring the weights of attributes and its estimate accuracy when combined with parametric or CBR estimation. (C) 2014 Elsevier B.V. All rights reserved.
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