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Transfer learning with a spatiotemporal graph convolution network for city flow prediction
Regular Papers | Updated：2025-03-13
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    • Transfer learning with a spatiotemporal graph convolution network for city flow prediction

      Enhanced Publication
    • 基于时空图卷积的城市流迁移预测
    • “In the field of smart city construction, a transfer learning method based on spatiotemporal graph convolution has been proposed. This method constructs a co-occurrence space between source and target domains and aligns the mapping of their data, achieving transfer learning of the source city flow prediction model on the target domain. It provides a new solution for cross-city bike flow prediction.”
    • Frontiers of Information Technology & Electronic Engineering   Vol. 26, Issue 1, Pages: 79-92(2025)

    • DOI：10.1631/FITEE.2300571    

      CLC： TP311;U495

    • Received：23 August 2023，

      Revised：11 December 2023，

      Published Online：27 December 2024，

      Published：2025-01

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  • Binkun LIU, Yu KANG, Yang CAO, et al. Transfer learning with a spatiotemporal graph convolution network for city flow prediction[J]. Frontiers of information technology & electronic engineering, 2025, 26(1): 79-92. DOI： 10.1631/FITEE.2300571.

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