Optimizing bike sharing system flows using graph mining, convolutional and recurrent neural networks (2020)
- Authors:
- Autor USP: KON, FABIO - IME
- Unidade: IME
- DOI: 10.1109/E-TEMS46250.2020.9111707
- Subjects: APRENDIZADO COMPUTACIONAL; APRENDIZAGEM PROFUNDA; ANÁLISE DE DADOS; ANÁLISE DE SÉRIES TEMPORAIS
- Keywords: data science; data visualization; bike-sharing systems; graph mining; time series prediction; recurrent neural networks; convolutional neural networks; shareable cities; urban informatics
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2020
- Source:
- Título: Proceedings
- Conference titles: IEEE European Technology and Engineering Management Summit - E-TEMS
- Status:
- Artigo possui versão em acesso aberto em repositório (Green Open Access)
- Versão do Documento:
- Versão submetida (Pré-print)
- Acessar versão aberta:
-
ABNT
LJUBENKOV, Davor e KON, Fábio e RATTI, Carlo. Optimizing bike sharing system flows using graph mining, convolutional and recurrent neural networks. 2020, Anais.. Piscataway: IEEE, 2020. Disponível em: https://doi.org/10.1109/E-TEMS46250.2020.9111707. Acesso em: 08 abr. 2026. -
APA
Ljubenkov, D., Kon, F., & Ratti, C. (2020). Optimizing bike sharing system flows using graph mining, convolutional and recurrent neural networks. In Proceedings. Piscataway: IEEE. doi:10.1109/E-TEMS46250.2020.9111707 -
NLM
Ljubenkov D, Kon F, Ratti C. Optimizing bike sharing system flows using graph mining, convolutional and recurrent neural networks [Internet]. Proceedings. 2020 ;[citado 2026 abr. 08 ] Available from: https://doi.org/10.1109/E-TEMS46250.2020.9111707 -
Vancouver
Ljubenkov D, Kon F, Ratti C. Optimizing bike sharing system flows using graph mining, convolutional and recurrent neural networks [Internet]. Proceedings. 2020 ;[citado 2026 abr. 08 ] Available from: https://doi.org/10.1109/E-TEMS46250.2020.9111707 - Dynamic resource management and automatic configuration of distributed component systems
- Using performance forecasting to accelerate elasticity
- Designing a maturity model for software startup ecosystems
- Dynamic resource allocation using performance forecasting
- Hadoop branching: architectural impacts on energy and performance
- Message from the CCGrid Workshops Chairs [Editorial]
- Early-stage software startups: main challenges and possible answers
- Using dynamic configuration to manage a scalable multimedia distribution system
- Apache sustained competitive advantage in the web server industry
- Batching: a design pattern for efficient and flexible client/server interaction
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Por se tratar de integração com serviço externo, podem existir diferentes versões do trabalho (como preprints ou postprints), que podem diferir da versão publicada.
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| 2999429.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
