Application of an Artificial Neural Network in Pavement Management System

Znanstveni rad - Prethodno/kratko priopćenje

• Autor: Josipa Domitrović
• Autor: Hrvoje Dragovan
• Autor: Tatjana Rukavina
• Autor: Sanja Dimter
• Autorova ustanova: Sveučilište Josipa Jurja Strossmayera u Osijeku; Građevinski i arhitektonski fakultet Osijek; (Zavod za geotehniku, prometnice i geodeziju)
• Autorova ustanova: Sveučilište u Zagrebu; Građevinski fakultet; (Zavod za prometnice)
• Znanstveno / umjetničko područje, polje i grana: TEHNIČKE ZNANOSTI; Građevinarstvo; Prometnice

Sažetak (engleski)

The era of intensive construction of new roads in Croatia is behind us. Today road agencies are focused on maintaining and preserving existing roads. Selection of an appropriate maintenance strategy is a complex task, which includes factors such as the current condition of the pavement, road classification, traffic volume etc. These factors are usually implemented in pavement management systems. The key components of pavement management systems are pavement performance prediction models such as artificial neural networks. This paper analyses the possibility of using artificial neural networks to evaluate existing pavement condition, and its possible application for defining the maintenance strategy of national roads. A backpropagation neural network was applied on 481.3 km of national roads in the Osijek-Baranja County. The obtained results indicated that artificial neural networks could be used for optimization of maintenance or rehabilitation strategies, and for the assessment of pavement condition at the project and network level.

• Ključne riječi (engleski): artificial neural network; backpropagation algorithm; pavement maintenance; pavement management system
• Jezik: engleski
• Vrsta publikacije: Znanstveni rad - Prethodno/kratko priopćenje
• Status objave: Objavljen
• Vrsta recenzije: Recenziran - međunarodna recenzija
• Verzija publikacije: Objavljena verzija rada (izdavačev PDF)
• Naslov časopisa: Tehnicki vjesnik - Technical Gazette
• Brojčani podaci: vol. 25, br. Supplement 2, str. 466-473
• p-ISSN: 1330-3651
• e-ISSN: 1848-6339
• DOI: https://doi.org/10.17559/TV-20150608121810
• URN:NBN: urn:nbn:hr:237:247361
• Datum objave publikacije: 2018
• URL dokumenta: https://hrcak.srce.hr/205945
• Vrsta resursa: Tekst
• Prava pristupa: Otvoreni pristup
• Datum i vrijeme pohrane: 2024-07-22 13:09:59