Urban Road Infrastructure Maintenance Planning with Application of Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F18%3APU128087" target="_blank" >RIV/00216305:26110/18:PU128087 - isvavai.cz</a>
Result on the web
<a href="https://www.hindawi.com/journals/complexity/2018/5160417/" target="_blank" >https://www.hindawi.com/journals/complexity/2018/5160417/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1155/2018/5160417" target="_blank" >10.1155/2018/5160417</a>
Alternative languages
Result language
angličtina
Original language name
Urban Road Infrastructure Maintenance Planning with Application of Neural Networks
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20101 - Civil engineering
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
COMPLEXITY
ISSN
1076-2787
e-ISSN
1099-0526
Volume of the periodical
neuveden
Issue of the periodical within the volume
2018
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
1-10
UT code for WoS article
000434857800001
EID of the result in the Scopus database
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