A Deep Learning Approach for Predicting Bus Passenger Demand Based on Weather Conditions Cover

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A Deep Learning Approach for Predicting Bus Passenger Demand Based on Weather Conditions

Transport and Telecommunication Journal

Volume 21 (2020): Issue 4 (December 2020)

By: Tânia Fontes, Ricardo Correia, Joel Ribeiro and José Luís Borges

Open Access

|Nov 2020

Authors

Tânia Fontes

tania.d.fontes@inesctec.pt

INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal

Ricardo Correia

ricardo.f.correia@inesctec.pt

INESC TEC and Faculty of Engineering, University of Porto, Porto, Portugal

Joel Ribeiro

joel.ribeiro@inesctec.pt

INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal

José Luís Borges

jlborges@fe.up.pt

INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal

DOI: https://doi.org/10.2478/ttj-2020-0020 | Journal eISSN: 1407-6179 | Journal ISSN: 1407-6160

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Language: English

Page range: 255 - 264

Published on: Nov 26, 2020

Published by: Transport and Telecommunication Institute

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

Urban public transport,

Bus passenger demand,

Weather conditions,

Artificial neural networks

Related subjects:

Introductions and overviews,

Engineering, other

© 2020 Tânia Fontes, Ricardo Correia, Joel Ribeiro, José Luís Borges, published by Transport and Telecommunication Institute
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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