Publicação
Machine learning approaches to bike-sharing systems
| dc.contributor.author | Albuquerque, Vitória | |
| dc.contributor.author | Dias, Miguel Sales | |
| dc.contributor.author | Bacao, Fernando | |
| dc.contributor.institution | NOVA Information Management School (NOVA IMS) | |
| dc.contributor.institution | Information Management Research Center (MagIC) - NOVA Information Management School | |
| dc.contributor.pbl | MDPI - Multidisciplinary Digital Publishing Institute | |
| dc.date.accessioned | 2021-06-05T00:14:53Z | |
| dc.date.available | 2021-06-05T00:14:53Z | |
| dc.date.issued | 2021-02 | |
| dc.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 | |
| dc.description.abstract | Cities 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. | en |
| dc.description.version | publishersversion | |
| dc.description.version | published | |
| dc.format.extent | 25 | |
| dc.format.extent | 4387723 | |
| dc.identifier.doi | 10.3390/ijgi10020062 | |
| dc.identifier.issn | 2220-9964 | |
| dc.identifier.other | PURE: 31783673 | |
| dc.identifier.other | PURE UUID: 712c1b8f-4a63-4b05-bec9-0a04a687a954 | |
| dc.identifier.other | Scopus: 85106531726 | |
| dc.identifier.other | WOS: 000622565400001 | |
| dc.identifier.other | ORCID: /0000-0002-0834-0275/work/153306413 | |
| dc.identifier.uri | http://hdl.handle.net/10362/118827 | |
| dc.identifier.url | https://www.scopus.com/pages/publications/85106531726 | |
| dc.identifier.url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000622565400001 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.subject | Bike-sharing systems | |
| dc.subject | Classification | |
| dc.subject | Machine learning | |
| dc.subject | Prediction | |
| dc.subject | PRISMA method | |
| dc.subject | Geography, Planning and Development | |
| dc.subject | Computers in Earth Sciences | |
| dc.subject | Earth and Planetary Sciences (miscellaneous) | |
| dc.subject | SDG 11 - Sustainable Cities and Communities | |
| dc.title | Machine learning approaches to bike-sharing systems | en |
| dc.title.subtitle | A systematic literature review | en |
| dc.type | journal article | |
| degois.publication.firstPage | 1 | |
| degois.publication.issue | 2 | |
| degois.publication.lastPage | 25 | |
| degois.publication.title | ISPRS International Journal of Geo-Information | |
| degois.publication.volume | 10 | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess |
Ficheiros
Principais
1 - 1 de 1
A carregar...
- Nome:
- Machine_Learning_Approaches_to_Bike_Sharing_Systems.pdf
- Tamanho:
- 4.18 MB
- Formato:
- Adobe Portable Document Format