Machine learning approaches to bike-sharing systems
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/118827 |
Resumo: | Albuquerque, V., Dias, M. S., & Bacao, F. (2021). Machine learning approaches to bike-sharing systems: A systematic literature review. ISPRS International Journal of Geo-Information, 10(2), 1-25. [62]. https://doi.org/10.3390/ijgi10020062 |
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7160 |
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Machine learning approaches to bike-sharing systemsA systematic literature reviewBike-sharing systemsClassificationMachine learningPredictionPRISMA methodGeography, Planning and DevelopmentComputers in Earth SciencesEarth and Planetary Sciences (miscellaneous)SDG 11 - Sustainable Cities and CommunitiesAlbuquerque, V., Dias, M. S., & Bacao, F. (2021). Machine learning approaches to bike-sharing systems: A systematic literature review. ISPRS International Journal of Geo-Information, 10(2), 1-25. [62]. https://doi.org/10.3390/ijgi10020062Cities are moving towards new mobility strategies to tackle smart cities’ challenges such as carbon emission reduction, urban transport multimodality and mitigation of pandemic hazards, emphasising on the implementation of shared modes, such as bike-sharing systems. This paper poses a research question and introduces a corresponding systematic literature review, focusing on machine learning techniques’ contributions applied to bike-sharing systems to improve cities’ mobility. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) method was adopted to identify specific factors that influence bike-sharing systems, resulting in an analysis of 35 papers published between 2015 and 2019, creating an outline for future research. By means of systematic literature review and bibliometric analysis, machine learning algorithms were identified in two groups: classification and prediction.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNAlbuquerque, VitóriaDias, Miguel SalesBacao, Fernando2021-06-05T00:14:53Z2021-022021-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article25application/pdfhttp://hdl.handle.net/10362/118827eng2220-9964PURE: 31783673https://doi.org/10.3390/ijgi10020062info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:01:35Zoai:run.unl.pt:10362/118827Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:43:57.429946Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Machine learning approaches to bike-sharing systems A systematic literature review |
title |
Machine learning approaches to bike-sharing systems |
spellingShingle |
Machine learning approaches to bike-sharing systems Albuquerque, Vitória Bike-sharing systems Classification Machine learning Prediction PRISMA method Geography, Planning and Development Computers in Earth Sciences Earth and Planetary Sciences (miscellaneous) SDG 11 - Sustainable Cities and Communities |
title_short |
Machine learning approaches to bike-sharing systems |
title_full |
Machine learning approaches to bike-sharing systems |
title_fullStr |
Machine learning approaches to bike-sharing systems |
title_full_unstemmed |
Machine learning approaches to bike-sharing systems |
title_sort |
Machine learning approaches to bike-sharing systems |
author |
Albuquerque, Vitória |
author_facet |
Albuquerque, Vitória Dias, Miguel Sales Bacao, Fernando |
author_role |
author |
author2 |
Dias, Miguel Sales Bacao, Fernando |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
NOVA Information Management School (NOVA IMS) Information Management Research Center (MagIC) - NOVA Information Management School RUN |
dc.contributor.author.fl_str_mv |
Albuquerque, Vitória Dias, Miguel Sales Bacao, Fernando |
dc.subject.por.fl_str_mv |
Bike-sharing systems Classification Machine learning Prediction PRISMA method Geography, Planning and Development Computers in Earth Sciences Earth and Planetary Sciences (miscellaneous) SDG 11 - Sustainable Cities and Communities |
topic |
Bike-sharing systems Classification Machine learning Prediction PRISMA method Geography, Planning and Development Computers in Earth Sciences Earth and Planetary Sciences (miscellaneous) SDG 11 - Sustainable Cities and Communities |
description |
Albuquerque, V., Dias, M. S., & Bacao, F. (2021). Machine learning approaches to bike-sharing systems: A systematic literature review. ISPRS International Journal of Geo-Information, 10(2), 1-25. [62]. https://doi.org/10.3390/ijgi10020062 |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-05T00:14:53Z 2021-02 2021-02-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/118827 |
url |
http://hdl.handle.net/10362/118827 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2220-9964 PURE: 31783673 https://doi.org/10.3390/ijgi10020062 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
25 application/pdf |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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