Residential buildings conceptual cost estimates with the use of support vector regression

Michał Juszczyk,V Andreev,T Matseevich,A Adamtsevich,A Ter-Martirosyan

doi:10.1051/matecconf/201819604090

Michał Juszczyk, V Andreev + Show 3 more

Open Access

https://doi.org/10.1051/matecconf/201819604090

Copy DOI

Journal: MATEC Web of Conferences	Publication Date: Jan 1, 2018
Citations: 4	License type: CC BY 4.0

Affiliation: Cracow University of Technology

Abstract

Cost analyses, and the conceptual cost estimates among them, are of the key importance for the construction projects successes. Implementation of neural networks or machine learning methods provides broad possibilities for this specific type of cost. The aim of the paper is to present some results of the studies on the use of support vector regression as a machine learning tool for conceptual cost estimates of residential buildings. Results for three models based on support vector regression and radial basis kernel functions are introduced.

Highlights

Cost estimation is one of the key processes in the course of a construction project
The ability to influence building’s characteristics and cost are the greater in the early design stage, than later in the course of the project. Both of the aforementioned stimulate the research on development models, that are based on various approaches and methods, capable of supporting conceptual cost estimates
The aim of this paper is to present the results of investigations on applicability of support vector regression (SVR) method for the purposes of residential buildings conceptual cost estimates

Summary

Introduction

Cost estimation is one of the key processes in the course of a construction project. Cost estimates serve for parties involved in a project as a basis for various decisions. Conceptual cost estimates, prepared in the early design stage are specific due to the two facts. The estimates have to rely on imprecise, incomplete information about the building. The ability to influence building’s characteristics and cost are the greater in the early design stage, than later in the course of the project. Both of the aforementioned stimulate the research on development models, that are based on various approaches and methods, capable of supporting conceptual cost estimates

Objectives

Results

Conclusion