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Pregled bibliografske jedinice broj: 741785

Application of Artificial Neural Network in a Pavement Management System


Dragovan, Hrvoje; Rukavina, Tatjana; Domitrović, Josipa
Application of Artificial Neural Network in a Pavement Management System // Road and Rail Infrastructure III / Lakušić, Stjepan (ur.).
Zagreb: Department of Transportation, Faculty of Civil Engineering, University of Zagreb, 2014. str. 211-217 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Application of Artificial Neural Network in a Pavement Management System

Autori
Dragovan, Hrvoje ; Rukavina, Tatjana ; Domitrović, Josipa

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Road and Rail Infrastructure III / Lakušić, Stjepan - Zagreb : Department of Transportation, Faculty of Civil Engineering, University of Zagreb, 2014, 211-217

Skup
3rd International Conference on Road and Rail Infrastructures - CETRA 2014

Mjesto i datum
Split, Hrvatska, 28-30.04.2014

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
artificial neural network; pavement management system; backpropagation algorithm; pavement maintenance

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Građevinarstvo



POVEZANOST RADA


Projekt / tema
082-1102147-2143 - Modeliranje ponašanje kolničkih konstrukcija cesta s asfaltnim zastorom (Tatjana Rukavina, )

Ustanove
Građevinski fakultet, Zagreb

Profili:

Avatar Url Tatjana Rukavina (autor)

Avatar Url Josipa Domitrović (autor)

Citiraj ovu publikaciju

Dragovan, Hrvoje; Rukavina, Tatjana; Domitrović, Josipa
Application of Artificial Neural Network in a Pavement Management System // Road and Rail Infrastructure III / Lakušić, Stjepan (ur.).
Zagreb: Department of Transportation, Faculty of Civil Engineering, University of Zagreb, 2014. str. 211-217 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Dragovan, H., Rukavina, T. & Domitrović, J. (2014) Application of Artificial Neural Network in a Pavement Management System. U: Lakušić, S. (ur.)Road and Rail Infrastructure III.
@article{article, editor = {Laku\v{s}i\'{c}, S.}, year = {2014}, pages = {211-217}, keywords = {artificial neural network, pavement management system, backpropagation algorithm, pavement maintenance}, title = {Application of Artificial Neural Network in a Pavement Management System}, keyword = {artificial neural network, pavement management system, backpropagation algorithm, pavement maintenance}, publisher = {Department of Transportation, Faculty of Civil Engineering, University of Zagreb}, publisherplace = {Split, Hrvatska} }