Publication detail

Early Fast Cost Estimates of Sewerage Projects Construction Costs Based on Ensembles of Neural Networks

JUSZCZYK, M. HANÁK, T. VÝSKALA, M. PACYNO, H. SIEJDA, M.

Original Title

Early Fast Cost Estimates of Sewerage Projects Construction Costs Based on Ensembles of Neural Networks

Type

journal article in Web of Science

Language

English

Original Abstract

his paper presents research results on the development of an original cost prediction model for construction costs in sewerage projects. The focus is placed on fast cost estimates applicable in the early stages of a project, based on fundamental information available during the initial design phase of sanitary sewers prior to the detailed design. The originality and novelty of this research lie in the application of artificial neural network ensembles, which include a combination of several individual neural networks and the use of simple averaging and generalized averaging approaches. The research resulted in the development of two ensemble-based models, including five neural networks that were trained and tested using data collected from 125 sewerage projects completed in the Czech Republic between 2018 and 2022. The data included information relevant to various aspects of projects and contract costs, updated to account for changes in costs over time. The developed models present satisfactory predictive performance, especially the ensemble model based on simple averaging, which offers prediction accuracy within the range of ±30% (in terms of percentage errors) for over 90% of the training and testing samples. The developed models, based on the ensembles of neural networks, outperformed the benchmark model based on the classical approach and the use of multiple linear regression.

Keywords

sewerage project; sanitary sewer networks; construction costs; construction project; early cost estimates; fast cost estimates; neural networks ensembles; artificial intelligence

Authors

JUSZCZYK, M.; HANÁK, T.; VÝSKALA, M.; PACYNO, H.; SIEJDA, M.

Released

28. 11. 2023

Publisher

MDPI

Location

Polsko

ISBN

2076-3417

Periodical

Applied Sciences - Basel

Year of study

13

Number

23

State

Swiss Confederation

Pages from

1

Pages to

24

Pages count

24

URL

Full text in the Digital Library

BibTex

@article{BUT185648,
  author="Michał {Juszczyk} and Tomáš {Hanák} and Miloslav {Výskala} and Hanna {Pacyno} and Michal {Siejda}",
  title="Early Fast Cost Estimates of Sewerage Projects Construction Costs Based on Ensembles of Neural Networks",
  journal="Applied Sciences - Basel",
  year="2023",
  volume="13",
  number="23",
  pages="1--24",
  doi="10.3390/app132312744",
  issn="2076-3417",
  url="https://www.mdpi.com/2076-3417/13/23/12744"
}