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Complexity
Volume 2017, Article ID 2450370, 13 pages
https://doi.org/10.1155/2017/2450370
Research Article

Estimation of Costs and Durations of Construction of Urban Roads Using ANN and SVM

University of Novi Sad, Faculty of Technical Sciences, Trg Dositeja Obradovica 6, Novi Sad, Serbia

Correspondence should be addressed to Igor Peško; sr.ca.snu@pbrogi

Received 27 June 2017; Accepted 12 September 2017; Published 7 December 2017

Academic Editor: Meri Cvetkovska

Copyright © 2017 Igor Peško et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Offer preparation has always been a specific part of a building process which has significant impact on company business. Due to the fact that income greatly depends on offer’s precision and the balance between planned costs, both direct and overheads, and wished profit, it is necessary to prepare a precise offer within required time and available resources which are always insufficient. The paper presents a research of precision that can be achieved while using artificial intelligence for estimation of cost and duration in construction projects. Both artificial neural networks (ANNs) and support vector machines (SVM) are analysed and compared. The best SVM has shown higher precision, when estimating costs, with mean absolute percentage error (MAPE) of 7.06% compared to the most precise ANNs which has achieved precision of 25.38%. Estimation of works duration has proved to be more difficult. The best MAPEs were 22.77% and 26.26% for SVM and ANN, respectively.