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Transportation Letters
The International Journal of Transportation Research
Volume 16, 2024 - Issue 3
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Research Article

Hybrid deep learning models for short-term demand forecasting of online car-hailing considering multiple factors

Siteng Lia Faculty of Maritime and Transportation, Ningbo University, Ningbo, China;b Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing, China;c The Sub-centre of National Traffic Management Engineering and Technology Research Centre Ningbo University Sub-center, Ningbo, ChinaView further author information
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Hang Yanga Faculty of Maritime and Transportation, Ningbo University, Ningbo, China;b Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing, China;c The Sub-centre of National Traffic Management Engineering and Technology Research Centre Ningbo University Sub-center, Ningbo, ChinaCorrespondence[email protected]
View further author information
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Rongjun Chenga Faculty of Maritime and Transportation, Ningbo University, Ningbo, China;b Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing, China;c The Sub-centre of National Traffic Management Engineering and Technology Research Centre Ningbo University Sub-center, Ningbo, ChinaView further author information
&
Hongxia Gea Faculty of Maritime and Transportation, Ningbo University, Ningbo, China;b Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing, China;c The Sub-centre of National Traffic Management Engineering and Technology Research Centre Ningbo University Sub-center, Ningbo, ChinaView further author information
Pages 218-233 | Received 08 Sep 2022, Accepted 28 Jan 2023, Published online: 20 Feb 2023

Citations (2)

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Read on this site (1)

Jiaming Liu, Xiaoya Tang & Haibin Liu. Enhanced forecasting of online car-hailing demand using an improved empirical mode decomposition with long short-term memory neural network. Transportation Letters 0:0, pages 1-17.
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Articles from other publishers (1)

Xiangmo Zhao, Kang Sun, Siyuan Gong & Xia Wu. (2023) RF-BiLSTM Neural Network Incorporating Attention Mechanism for Online Ride-Hailing Demand Forecasting. Symmetry 15:3, pages 670.
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