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Scientific paper - Preliminary note / Short communication
Application of an Artificial Neural Network in Pavement Management System
Road and Rail Infrastructure III, - (2018), -; 211-217. urn:nbn:hr:237:541577
Dragovan, Hrvoje; Rukavina, Tatjana; Domitrović, Josipa

Institutional repository: Repository of the Faculty of Civil Engineering, University of Zagreb

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Dragovan, H., Rukavina, T. & Domitrović, J. (2018). Application of an Artificial Neural Network in Pavement Management System. Road and Rail Infrastructure III, -. (-), 211-217. Retrieved from https://urn.nsk.hr/urn:nbn:hr:237:541577

Dragovan, Hrvoje, et al. "Application of an Artificial Neural Network in Pavement Management System." Road and Rail Infrastructure III, vol. -, no. -, 2018, pp. 211-217. https://urn.nsk.hr/urn:nbn:hr:237:541577

Dragovan, Hrvoje, Tatjana Rukavina and Josipa Domitrović. "Application of an Artificial Neural Network in Pavement Management System." Road and Rail Infrastructure III -, no. - (2018): 211-217. https://urn.nsk.hr/urn:nbn:hr:237:541577

Dragovan, H., Rukavina, T. and Domitrović, J. (2018) 'Application of an Artificial Neural Network in Pavement Management System', Road and Rail Infrastructure III, -(-), pp. 211-217. Available at: https://urn.nsk.hr/urn:nbn:hr:237:541577 (Accessed 24 November 2024)

Dragovan H, Rukavina T, Domitrović J. Application of an Artificial Neural Network in Pavement Management System. Road and Rail Infrastructure III [Internet]. 2018 [cited 2024 November 24];-(-):211-217. Available at: https://urn.nsk.hr/urn:nbn:hr:237:541577

H. Dragovan, T. Rukavina and J. Domitrović, "Application of an Artificial Neural Network in Pavement Management System", Road and Rail Infrastructure III, vol. -, no. -, pp. 211-217, 2018. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:237:541577. [Accessed: 24 November 2024]

Metadata
Title (english)Application of an Artificial Neural Network in Pavement Management System
AuthorHrvoje Dragovan
AuthorTatjana Rukavina
AuthorJosipa Domitrović
Author's institutionUniversity of Zagreb
Faculty of Civil Engineering
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Civil Engineering
Abstract (english)
The era of intensive construction of new roads is behind us, so road agencies are now focused on maintaining and preserving existing pavement surfaces. As they are faced with limited founds for maintenance it is important to utilize the money by selecting the best maintenance strategy. Selection of appropriate maintenance strategy is a complex task which includes factors such as current condition of the pavement, road classification, traffic volume and type of pavement distress. These factors can be automated and implemented in pavement management systems to achieve standardised approach to road pavement assessment and management. One of the key components of a pavement management systems are pavement performance prediction models which simulate pavement deterioration process and forecast its condition over time, one of such model is artificial neural network. This paper analyzes the possibility of using artificial neural networks in pavement management systems for evaluation of existing pavement condition and its possible application for defining the maintenance strategy of state roads. Backpropagation algorithm was applied on 481, 3 km of state road in Osijek-Baranja County which represents 7% of total length of national road network in Croatia. Obtained results indicated that artificial neural networks can be used for optimization of maintenance or rehabilitation strategies as well as assessment of pavement condition at project and network level.
Keywords (english)
Languageenglish
Publication typeScientific paper - Preliminary note / Short communication
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleRoad and Rail Infrastructure III
Numberingvol. -, no. -, pp. 211-217
p-ISSN1848-9842
URN:NBNurn:nbn:hr:237:541577
Publication2018
Type of resourceText
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-09-05 10:09:30