Knowledge adaptation with model sharing for passenger demand forecasting

Authors

S. Travis Waller (ORCID: https://orcid.org/0000-0002-2939-2090)
Lei Bai (ORCID: https://orcid.org/0000-0003-3378-7201)
Lina Yao (ORCID: https://orcid.org/0000-0002-4149-839X)
Can Li (ORCID: https://orcid.org/0000-0002-0039-2839)
Wei Liu (ORCID: https://orcid.org/0000-0001-8638-3695)

Institutions

Tongji University (CN)
Commonwealth Scientific and Industrial Research Organisation (AU)
Hong Kong Polytechnic University (HK)
ShangHai JiAi Genetics & IVF Institute (CN)
Shanghai Artificial Intelligence Laboratory (CN)
Technische Universität Dresden (DE)

Publication Details

Journal: Transportmetrica A Transport Science
Published: 2025-05-06
DOI: https://doi.org/10.1080/23249935.2025.2499862
Primary Topic: Traffic Prediction and Management Techniques
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Natural Science Foundation of China
Hong Kong Polytechnic University

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article

Knowledge adaptation with model sharing for passenger demand forecasting

S. Travis Waller, Lei Bai, Lina Yao, Can Li et al.

May 6, 2025

Transportmetrica A Transport Science

Traffic Prediction and Management Techniques

article

Knowledge adaptation with model sharing for passenger demand forecasting

S. Travis Waller, Lei Bai, Lina Yao, Can Li, Wei Liu

May 6, 2025article en

Abstract

No abstract available for this paper.

Transportmetrica A Transport Science

Tongji University (CN), Commonwealth Scientific and Industrial Research Organisation (AU), Hong Kong Polytechnic University (HK), ShangHai JiAi Genetics & IVF Institute (CN), Shanghai Artificial Intelligence Laboratory (CN), Technische Universität Dresden (DE)

National Natural Science Foundation of China, Hong Kong Polytechnic University

Openalex Percentile: Top 91%

Traffic Prediction and Management Techniques

DOI Source OpenAlex

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