Publication detail

Urban Road Infrastructure Maintenance Planning with Application of Neural Networks

MAROVIĆ, I. ANDROJIĆ, I. JAJAC, N. HANÁK, T.

Original Title

Urban Road Infrastructure Maintenance Planning with Application of Neural Networks

Type

journal article in Web of Science

Language

English

Original Abstract

The maintenance planning within the urban road infrastructure management is a complex problem from both the management and technoeconomic aspects. The focus of this research is on decision-making processes related to the planning phase during management of urban road infrastructure projects. The goal of this research is to design and develop an ANN model in order to achieve a successful prediction of road deterioration as a tool for maintenance planning activities. Such a model is part of the proposed decision support concept for urban road infrastructure management and a decision support tool in planning activities. The input data were obtained from Circly 6.0 Pavement Design Software and used to determine the stress values (560 testing combinations). It was found that it is possible and desirable to apply such a model in the decision support concept in order to improve urban road infrastructure maintenance planning processes.

Keywords

road infrastructure, maintenance, planning, neural networks

Authors

MAROVIĆ, I.; ANDROJIĆ, I.; JAJAC, N.; HANÁK, T.

Released

4. 6. 2018

Publisher

Hindawi

Location

Velká Británie

ISBN

1076-2787

Periodical

COMPLEXITY

Number

2018

State

United States of America

Pages from

1

Pages to

10

Pages count

10

URL

http://dx.doi.org/10.1155/2018/5160417

Full text in the Digital Library

http://hdl.handle.net/11012/83696

BibTex

@article{BUT147934,
  author="Ivan {Marović} and Ivica {Androjić} and Nikša {Jajac} and Tomáš {Hanák}",
  title="Urban Road Infrastructure Maintenance Planning with Application of Neural Networks",
  journal="COMPLEXITY",
  year="2018",
  number="2018",
  pages="1--10",
  doi="10.1155/2018/5160417",
  issn="1076-2787",
  url="http://dx.doi.org/10.1155/2018/5160417"
}