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Descripción
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| Grouping urban bus routes is necessary when there are evidences of significant differences among them. In Jiménez et al. (2013), a reduced sample of routes was grouped into clusters utilizing kinematic measured data. As a further step, in this paper, the remaining urban bus routes of a city, for which no kinematic measurements are available, are classified. For such purpose we use macroscopic geographical and functional variables to describe each route, while the clustering process is performed by means of a neural network. Limitations caused by reduced training samples are solved using the bootstrap method. | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Transportation Research Part D: Transport and Environment |
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ISSN
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1361-9209 |
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Factor de impacto JCR
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1,801 |
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Información de impacto
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Volumen
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30 |
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DOI
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10.1016/j.trd.2014.05.008 |
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Número de revista
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july 2014 |
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Desde la página
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32 |
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Hasta la página
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37 |
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Mes
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JULIO |
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Ranking
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