Descripción
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This paper presents a new approach that designs the flow of passengers in mass transportation systems in presence of uncertainties. One of the techniques used for the prediction of passenger demand is the origindestination matrices. However, this method is limited to urban areas and rarely to explicit stations. Otherwise, the gravity models based on friction functions can be another alternative; however, it is difficult to fit into practical achievements. Another solution might be the application of artificial intelligence techniques so as to include some intuitive knowledge provided by an expert to predict the flow demand of passengers¿ trips in explicit stations. This paper proposes to combine a matrix of origin-destination trips of travel zones, with the intuitive knowledge, applying a fuzzy logic inference approach. | |
Internacional
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Si |
Nombre congreso
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International Conference on Fuzzy Computation, ICFC 2010 International Conference on Neural Computation, ICNC 2010 |
Tipo de participación
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960 |
Lugar del congreso
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Valencia, (Spain) |
Revisores
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Si |
ISBN o ISSN
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978-989-8425-32-4 |
DOI
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Fecha inicio congreso
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24/10/2010 |
Fecha fin congreso
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26/10/2010 |
Desde la página
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1 |
Hasta la página
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4 |
Título de las actas
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Proceedings of the International Conference on Fuzzy Computation and International Conference on Neural Computation |