A mixture model clustering approach for temporal passenger pattern characterization in public transport

Anne-Sarah Briand, Etienne Côme, Mohamed K. El Mahrsi, Latifa Oukhellou

Open source

DOI: 10.1007/s41060-015-0002-x
Published: 2016-01-18
Container: International Journal of Data Science and Analytics
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s41060-015-0002-x,
  title = {A mixture model clustering approach for temporal passenger pattern characterization in public transport},
  author = {Anne-Sarah Briand and Etienne Côme and Mohamed K. El Mahrsi and Latifa Oukhellou},
  year = {2016},
  journal = {International Journal of Data Science and Analytics},
  doi = {10.1007/s41060-015-0002-x},
  url = {https://doi.org/10.1007/s41060-015-0002-x}
}

RIS

TY  - JOUR
TI  - A mixture model clustering approach for temporal passenger pattern characterization in public transport
AU  - Anne-Sarah Briand
AU  - Etienne Côme
AU  - Mohamed K. El Mahrsi
AU  - Latifa Oukhellou
PY  - 2016
JO  - International Journal of Data Science and Analytics
DO  - 10.1007/s41060-015-0002-x
UR  - https://doi.org/10.1007/s41060-015-0002-x
ER  -

APA

Briand, A., Côme, E., Mahrsi, M. K. E., & Oukhellou, L. (2016). A mixture model clustering approach for temporal passenger pattern characterization in public transport. International Journal of Data Science and Analytics. https://doi.org/10.1007/s41060-015-0002-x

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crossref · retrieved 2026-09-26T04:21:40.407Z