Spatio-temporal fusion and contrastive learning for urban flow prediction

[PDF] arxiv.org

Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook

X Zou, Y Yan, X Hao, Y Hu, H Wen, E Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …
被引用次数：5 相关文章 所有 3 个版本

DeepWind: a heterogeneous spatio-temporal model for wind forecasting

B Wang, J Shi, B Tan, M Ma, F Hong, Y Yu… - Knowledge-Based Systems, 2024 - Elsevier
Deep learning (DL) has shown great potential in enhancing the performance of traditional
numerical weather prediction (NWP) methods in weather forecasting. Certain applications …
被引用次数：1 相关文章 所有 3 个版本
[PDF] arxiv.org

Fine-Grained Urban Flow Inference with Multi-scale Representation Learning

S Yuan, D Li, W Liu, X Zhang, M Chen, J Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
Fine-grained urban flow inference (FUFI) is a crucial transportation service aimed at
improving traffic efficiency and safety. FUFI can infer fine-grained urban traffic flows based …
相关文章