Wang, Rui and Hafez, Salleh and Zulkiflee, Abdul Samad and Nabilah Filzah, Mohd Radzuan and Wen, Kok Ching (2024) Fundamentals of developing conceptual cost estimation models using machine learning techniques: Selection and measurement of building attributes. Journal of the Malaysian Institute of Planners, 22 (3). pp. 242-256. ISSN 1675-6215. (Published)
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Abstract
Ensuring the identification of building attributes is the primary task in developing a machine learning cost estimation model. However, the existing research on building attributes has the following shortcomings: it struggles to categorize building characteristics according to various cost types, and the suggested sets of attributes do not clearly establish measurement standards for these qualities. To address these issues, this study aims to select a set of building attributes suitable for conceptual cost estimation and establishment of measurement standards. Through a two-round process of focused group discussions, this research ultimately identified 13 building attributes that can be collected before the completion of building design. These attributes serve as a basis for assessing completed building projects during the model development phase and for evaluating new projects during the model application phase. This study provides a foundational framework for the development of conceptual cost estimation models, ultimately enhancing the accuracy of machine learning cost estimation models.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Conceptual cost estimation, machine learning, building attributes |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Faculty/Division: | Faculty of Computing |
| Depositing User: | Miss Amelia Binti Hasan |
| Date Deposited: | 13 Aug 2024 01:11 |
| Last Modified: | 13 Aug 2024 01:11 |
| URI: | http://umpir.ump.edu.my/id/eprint/42323 |
| Download Statistic: | View Download Statistics |
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