Predicting Hourly Boarding Demand of Bus Passengers Using Imbalanced Records From Smart-Cards: A Deep Learning Approach-Reference-Cited by-同舟云学术

Predicting Hourly Boarding Demand of Bus Passengers Using Imbalanced Records From Smart-Cards: A Deep Learning Approach

Author:

Tang Tianli¹^ORCID,Liu Ronghui¹^ORCID,Choudhury Charisma²,Fonzone Achille³^ORCID,Wang Yuanyuan⁴^ORCID

Affiliation:

1. School of Transportation, Southeast University, Nanjing, China

2. Institute for Transport Studies, University of Leeds, Leeds, U.K

3. Transport Research Institute, Edinburgh Napier University, Edinburgh, U.K

4. School of Business Administration, Zhejiang University of Finance and Economics, Hangzhou, China

Funder

National Natural Science Foundation of China

Key Project of National Natural Science Foundation of China

Project of Jiangsu Funding Program for Excellent Postdoctoral Talent

UKRI Future Leader Fellowship, U.K.

Natural Science Foundation of Zhejiang Province

Humanities and Social Sciences Fund of the Ministry of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

Reference82 articles.

3. Modelling urban bus service and passenger reliability;liu;3rd Int Symp Transp Netw Rel,2007

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