Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/56365
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cristóbal, Teresa | en_US |
dc.contributor.author | Padrón Morales, Gabino | en_US |
dc.contributor.author | Quesada Arencibia, Francisco Alexis | en_US |
dc.contributor.author | Alayón Hernández, Francisco Javier | en_US |
dc.contributor.author | De Blasio , Gabriele Salvatore | en_US |
dc.contributor.author | García Rodríguez, Carmelo Rubén | en_US |
dc.date.accessioned | 2019-08-21T18:03:54Z | - |
dc.date.available | 2019-08-21T18:03:54Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.issn | 2504-3900 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/56365 | - |
dc.description.abstract | Travel Time plays a key role in the quality of service in road-based mass transit systems. In this type of mass transit systems, travel time of a public transport line is the sum of the dwell time at each bus stop and the nonstop running time between pair of consecutives bus stops of the line. The aim of the methodology presented in this paper is to obtain the behavior patterns of these times. Knowing these patterns, it would be possible to reduce travel time or its variability to make more reliable travel time predictions. To achieve this goal, the methodology uses data related to check-in and check-out movements of the passengers and vehicles GPS positions, processing this data by Data Mining techniques. To illustrate the validity of the proposal, the results obtained in a case of use in presented. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Proceedings (MDPI) | en_US |
dc.source | Proceedings (MDPI) [ISSN 2504-3900], v. 2 (19), 1217 | en_US |
dc.subject | 3327 Tecnología de los sistemas de transporte | en_US |
dc.subject | 120304 Inteligencia artificial | en_US |
dc.subject.other | Road-based mass transit systems | en_US |
dc.subject.other | Travel time | en_US |
dc.subject.other | Intelligent transport systems | en_US |
dc.subject.other | Big data | en_US |
dc.subject.other | Data mining | en_US |
dc.subject.other | Pattern clustering | en_US |
dc.title | Using data mining to analyze dwell time and nonstop running time in road-based mass transit systems | en_US |
dc.type | info:eu-repo/semantics/article | en_US |
dc.type | Article | en_US |
dc.relation.conference | 12th International Conference on Ubiquitous Computing and Ambient Intelligence - UCAmI 2018 | - |
dc.identifier.doi | 10.3390/proceedings2191217 | en_US |
dc.identifier.issue | 19 | - |
dc.description.firstpage | 1217 | en_US |
dc.relation.volume | 2 | en_US |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Artículo | en_US |
dc.utils.revision | Sí | en_US |
dc.identifier.ulpgc | Sí | en_US |
dc.contributor.buulpgc | BU-INF | en_US |
item.fulltext | Con texto completo | - |
item.grantfulltext | open | - |
crisitem.author.dept | GIR IUCES: Computación inteligente, percepción y big data | - |
crisitem.author.dept | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.dept | GIR IUCES: Computación inteligente, percepción y big data | - |
crisitem.author.dept | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.dept | GIR IUCES: Computación inteligente, percepción y big data | - |
crisitem.author.dept | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.dept | GIR IUCES: Computación inteligente, percepción y big data | - |
crisitem.author.dept | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.dept | GIR IUCES: Computación inteligente, percepción y big data | - |
crisitem.author.dept | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.orcid | 0000-0002-5573-1156 | - |
crisitem.author.orcid | 0000-0002-8313-5124 | - |
crisitem.author.orcid | 0000-0002-7285-9194 | - |
crisitem.author.orcid | 0000-0002-6233-567X | - |
crisitem.author.orcid | 0000-0003-1433-3730 | - |
crisitem.author.parentorg | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.parentorg | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.parentorg | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.parentorg | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.parentorg | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.fullName | Padrón Morales, Gabino | - |
crisitem.author.fullName | Quesada Arencibia, Francisco Alexis | - |
crisitem.author.fullName | Alayón Hernández,Francisco Javier | - |
crisitem.author.fullName | De Blasio, Gabriele Salvatore | - |
crisitem.author.fullName | García Rodríguez, Carmelo Rubén | - |
crisitem.event.eventsstartdate | 04-12-2018 | - |
crisitem.event.eventsenddate | 07-12-2018 | - |
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