Detail publikace

Urban Road Infrastructure Maintenance Planning with Application of Neural Networks

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

Originální název

Urban Road Infrastructure Maintenance Planning with Application of Neural Networks

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

road infrastructure, maintenance, planning, neural networks

Autoři

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

Vydáno

4. 6. 2018

Nakladatel

Hindawi

Místo

Velká Británie

ISSN

1076-2787

Periodikum

COMPLEXITY

Číslo

2018

Stát

Spojené státy americké

Strany od

1

Strany do

10

Strany počet

10

URL

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

Plný text v Digitální knihovně

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"
}