Modeling Commuter’s Sociodemographic Characteristics to Predict Public Transport Usage Frequency by Applying Supervised Machine Learning Method Cover

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Modeling Commuter’s Sociodemographic Characteristics to Predict Public Transport Usage Frequency by Applying Supervised Machine Learning Method

Transport technic and technology

Volume 15 (2019): Issue 2 (December 2019)

By: Nabeel Shakeel, Farrukh Baig and Muhammad Abubakar Saddiq

Open Access

|Dec 2019

Authors

Nabeel Shakeel

plannernabeel@buaa.edu.cn

MoE Key Laboratory of Complex System Analysis and Management Decision, School of Economics and Management, Beihang University, Beijing, China

Department of City and Regional Planning, University of Engineering and Technology, Lahore, Pakistan

Farrukh Baig

farrukhbaig@mail.dlut.edu.cn

School of Transportation and Logistics, Dalian University of Technology, Dalian, China

Muhammad Abubakar Saddiq

abubakar@buaa.edu.cn

School of Computer Sciences and Engineering, Beihang University, Beijing, China

DOI: https://doi.org/10.2478/ttt-2019-0005 | Journal eISSN: 2585-8084

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Language: English

Page range: 1 - 7

Published on: Dec 30, 2019

Published by: Univesity of Žilina

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

machine learning,

public transport,

socio-demographic status,

Related subjects:

Computer sciences,

Information technology,

Business and economics,

Business management,

Business management, other,

Transportation, logistics, air traffic, shipping,

Mechanical engineering,

© 2019 Nabeel Shakeel, Farrukh Baig, Muhammad Abubakar Saddiq, published by Univesity of Žilina
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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