MATEC Web Conf.
Volume 196, 2018XXVII R-S-P Seminar, Theoretical Foundation of Civil Engineering (27RSP) (TFoCE 2018)
|Number of page(s)||7|
|Section||Building Materials, Technologies, Organization and Management in Construction|
|Published online||03 September 2018|
Residential buildings conceptual cost estimates with the use of support vector regression
Cracow University of Technology, Faculty of Civil Engineering,
Corresponding author: firstname.lastname@example.org
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.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.