The challenges of nonparametric cost estimation of construction works with the use of artificial intelligence tools
Authors:
- Michał Juszczyk
Abstract
Nonparametric cost estimation in construction projects with the use of artificial networks is presented as suitable mainly for the early estimates. These conceptual estimates are based on the variables – namely cost predictors that characterize the project or a facility. Data gathered on the basis of completed projects are combined together and applied to the current project cost estimation process. The aim of the paper is to discuss the opportunities and challenges of the approach based on the artificial intelligence tools to cost estimation of construction works. The proposed approach is based on the concept of nonparametric cost estimation and application of artificial neural networks. The author's idea and intention is to transfer the mechanisms of nonparametric cost estimating to the level of construction works. Neural networks, due to their general capabilities, seem to be a good tool to aid the proposed approach. The paper contains discussion of the proposed approach and its applicability.
- Record ID
- CUTda488b129c5a4ae5bd20e67d79cddb3f
- Publication categories
- ; ;
- Author
- Journal series
- Procedia Engineering, ISSN 1877-7058
- Issue year
- 2017
- Vol
- 196
- Pages
- 415-422
- Other elements of collation
- schem.; tab.; Bibliografia (na s.) - 421-422; Bibliografia (liczba pozycji) - 25; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 196
- Conference
- Creative Construction Conference 2017 (CCC 2017), 2017, 19-06-2017 - 22-06-2017, Primosten, Chorwacja
- Keywords in English
- artificial intelligence, neural networks, construction works, nonparametric cost estimation
- DOI
- DOI:10.1016/j.proeng.2017.07.218 Opening in a new tab
- URL
- https://doi.org/10.1016/j.proeng.2017.07.218 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 15
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTda488b129c5a4ae5bd20e67d79cddb3f/
- URN
urn:pkr-prod:CUTda488b129c5a4ae5bd20e67d79cddb3f
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.