Descripción
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In line with the principles of the European Commission's European 2020 Strategy (COM: 2010), it is essential to establish intelligent, sustainable and inclusive transport networks that enhance the social development and territorial cohesion of the Union. In this context, ports are called upon to Contribute to a more sustainable mobility of goods. The number of variables to be considered in order to carry out the decision making and to make the management of the ports sustainable is very large. However, this handicap can be saved through the use of Bayesian networks because they allow modeling uncertainty probabilistically even when the number of variables is high. The fundamental task in Bayesian Networks is inference, observations are used to update or infer the probability that a hypothesis may be true. In making the analysis, the main conclusion drawn is that variables of institutional type are closely related to each other and knowing one or several of them, it is possible to determine 'a posteriori' probability of the others. | |
Internacional
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Si |
Nombre congreso
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The 5th QUAESTI Scientific Conference - Multidisciplinary Studies and Approaches. |
Tipo de participación
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960 |
Lugar del congreso
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Zillina (Slovakia) |
Revisores
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Si |
ISBN o ISSN
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978-80-554-1407-2 |
DOI
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10.18638/quaesti.2017.5.1.311 |
Fecha inicio congreso
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09/12/2017 |
Fecha fin congreso
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16/12/2017 |
Desde la página
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142 |
Hasta la página
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146 |
Título de las actas
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Proceeding in QUAESTI 2017 |