W Jiang, J Luo - Expert systems with applications, 2022 - Elsevier
Traffic forecasting is important for the success of intelligent transportation systems. Deep learning models, including convolution neural networks and recurrent neural networks, have …
As a core technology of Intelligent Transportation System, traffic flow prediction has a wide range of applications. The fundamental challenge in traffic flow prediction is to effectively …
Z Gao, C Tan, L Wu, SZ Li - … of the IEEE/CVF conference on …, 2022 - openaccess.thecvf.com
Abstract From CNN, RNN, to ViT, we have witnessed remarkable advancements in video prediction, incorporating auxiliary inputs, elaborate neural architectures, and sophisticated …
The prediction of crowd flows is an important urban computing issue whose purpose is to predict the future number of incoming and outgoing people in regions. Measuring the …
Z Fang, Q Long, G Song, K Xie - Proceedings of the 27th ACM SIGKDD …, 2021 - dl.acm.org
Spatial-temporal forecasting has attracted tremendous attention in a wide range of applications, and traffic flow prediction is a canonical and typical example. The complex and …
The predictive learning of spatiotemporal sequences aims to generate future images by learning from the historical context, where the visual dynamics are believed to have modular …
F Li, J Feng, H Yan, G Jin, F Yang, F Sun… - ACM Transactions on …, 2023 - dl.acm.org
Traffic prediction is the cornerstone of intelligent transportation system. Accurate traffic forecasting is essential for the applications of smart cities, ie, intelligent traffic management …
C Song, Y Lin, S Guo, H Wan - Proceedings of the AAAI conference on …, 2020 - ojs.aaai.org
Spatial-temporal network data forecasting is of great importance in a huge amount of applications for traffic management and urban planning. However, the underlying complex …
J Ji, J Wang, C Huang, J Wu, B Xu, Z Wu… - Proceedings of the …, 2023 - ojs.aaai.org
Robust prediction of citywide traffic flows at different time periods plays a crucial role in intelligent transportation systems. While previous work has made great efforts to model …