C Wang, Y Liang, G Tan - … of the 30th International Conference on …, 2022 - dl.acm.org
Crowd flow forecasting, which aims to predict the crowds entering or leaving certain regions, is a fundamental task in smart cities. One of the key properties of crowd flow data is …
Deep recommender systems (DRS) are critical for current commercial online service providers, which address the issue of information overload by recommending items that are …
Accurate traffic volume prediction plays a crucial role in urban traffic control by relieving congestion through improved regulation of traffic volume. Network‐level traffic volume …
Sensors in cyber-physical systems often capture interconnected processes and thus emit correlated time series (CTS), the forecasting of which enables important applications. The …
C Wang, Y Liang, G Tan - Proceedings of the 17th ACM International …, 2024 - dl.acm.org
Citywide spatio-temporal (ST) forecasting is a fundamental task for many urban applications, including traffic accident prediction, taxi demand planning, and crowd flow forecasting. The …
Spatio-temporal forecasting is of great importance in a wide range of dynamic systems applications, such as earth science, transport planning, etc. These applications rely on …
X Zhang, Q Jin, S Xiang, C Pan - IEEE Geoscience and Remote …, 2022 - ieeexplore.ieee.org
Exploiting deep learning for the meteorological forecasting (MF) task is challenging due to the complex spatio-temporal correlation, non-stationarity, and imbalanced data distribution …
J Deng, X Chen, R Jiang, D Yin, Y Yang… - … on Knowledge and …, 2024 - ieeexplore.ieee.org
Multivariate time-series (MTS) forecasting is a paramount and fundamental problem in many real-world applications. The core issue in MTS forecasting is how to effectively model …
M Chang, Z Ding, Z Zhao, Z Cai - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Traffic patterns in the spatiotemporal network are affected by temporal dynamics and spatial correlations. The network flows have different strengths interacting at various implicit layers …