Predictive Performance of Building Construction Estimation: An Analysis based on ANN Model
- Authors
- Yun, S.
- Issue Date
- 2022
- Publisher
- Success Culture Press
- Keywords
- ANN; cost estimation; model
- Citation
- Journal of System and Management Sciences, v.12, no.2, pp.331 - 341
- Indexed
- SCOPUS
- Journal Title
- Journal of System and Management Sciences
- Volume
- 12
- Number
- 2
- Start Page
- 331
- End Page
- 341
- URI
- https://scholarworks.bwise.kr/gnu/handle/sw.gnu/2641
- DOI
- 10.33168/JSMS.2022.0216
- ISSN
- 1816-6075
- Abstract
- "Recently, various technologies capable of implementing artificial intelligence have been developed along with the expansion of interest in machine learning. Efforts are also being made to introduce various machine learning technologies in the construction field. The most important thing in the construction field is construction costs, and technologies that can be used practically in predicting construction costs have not been developed. The learning model of construction cost prediction can be composed of various elements, and depending on these factors, the prediction performance is greatly affected. In this study, the influencing factors affecting the prediction of construction costs are derived, and based on these, the change in construction cost prediction performance according to the depth of the Artificial Neural Network (ANN) model and the configuration of the node is analyzed. The construction cost prediction model based on machine learning is expected to help predict and analyze construction costs more accurately and quickly in the future. ? 2022, Success Culture Press. All rights reserved.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - 공과대학 > School of Architectural Engineering > Journal Articles

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.