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A preliminary estimate of time and cost in urban road construction using neural networks

Igor Peško orcid id orcid.org/0000-0001-9098-3642 ; University of Novi Sad, Faculty of Technical Sciences, Department of Civil Engineering and Geodesy, Trg Dositeja Obradovica 6, 21000 Novi Sad, Republic of Serbia
Milan Trivunić ; University of Novi Sad, Faculty of Technical Sciences, Department of Civil Engineering and Geodesy, Trg Dositeja Obradovica 6, 21000 Novi Sad, Republic of Serbia
Goran Cirović orcid id orcid.org/0000-0001-7419-8695 ; University of Belgrade, Belgrade University College of Applied Studies in Civil Engineering and Geodesy, Department of Civil Engineering, Hajduk Stankova 2, 11000 Belgrade, Republic of Serbia
Vladimir Mučenski orcid id orcid.org/0000-0001-9830-4747 ; University of Novi Sad, Faculty of Technical Sciences, Department of Civil Engineering and Geodesy, Trg Dositeja Obradovica 6, 21000 Novi Sad, Republic of Serbia


Puni tekst: hrvatski pdf 1.055 Kb

str. 563-570

preuzimanja: 684

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Puni tekst: engleski pdf 1.055 Kb

str. 563-570

preuzimanja: 564

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Sažetak

Business carried out by construction companies is based on the implementation of agreed projects within the agreed cost and time limits. The contractor's estimation of a project goes through several phases. A preliminary estimate of the duration and cost of a construction is essential and is the first phase of the estimate, in fact, it is one of the most important phases considering that it is the basis for any decision concerning involvement in the potential project. The contractor’s reply to the investor regarding involvement in the potential project must be submitted on time, it must be accurate enough and with the minimum cost invested in the analysis. Analyses conducted within the research presented in this paper confirm that artificial neural networks (ANN) offer the possibility of satisfying all three criteria. That is, ANNs provide satisfactory accuracy for the preliminary estimate of the duration and cost of projects with the minimum engagement of resources to implement the above analysis.

Ključne riječi

artificial neural networks; cost and duration estimation; normalization; road construction

Hrčak ID:

104086

URI

https://hrcak.srce.hr/104086

Datum izdavanja:

15.6.2013.

Podaci na drugim jezicima: hrvatski

Posjeta: 2.206 *