Artificial neural network as a support of platform track assignment within simulation models reflecting passenger railway stations
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F09%3A00009520" target="_blank" >RIV/00216275:25530/09:00009520 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Artificial neural network as a support of platform track assignment within simulation models reflecting passenger railway stations
Original language description
Simulation models reflecting the operation of transportation systems are supposed to utilize an appropriate realization of decision-making procedures. The formation or selection of adequate modelling approaches and methodologies has to be done in this context. Attention is paid to a specific operational problem related to the assignment of platform tracks to delayed arriving trains within simulation models of passenger railway stations. The application of a twolayered artificial neural network as a decision-making support associated with the mentioned assignment problem was investigated. The neural network reached very encouraging results with regard to the studied problem, which enables its profitable utilization. It means, in fact, that the quality of relevant simulation models rises and the consequent credibility of corresponding simulation studies for railway companies should be increased.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JO - Land transport systems and equipment
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Rail and Rapid Transit
ISSN
0954-4097
e-ISSN
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Volume of the periodical
2009
Issue of the periodical within the volume
F5
Country of publishing house
GB - UNITED KINGDOM
Number of pages
11
Pages from-to
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UT code for WoS article
000270798000008
EID of the result in the Scopus database
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