A novel stochastic configuration network with enhanced feature extraction for industrial process modeling
Q Wang, W Yang, W Dai, X Ma - Neurocomputing, 2024 - Elsevier
Stochastic configuration networks (SCNs), possessing sound generalization performance
and low computational burden, have been extensively investigated in data analysis field. But …
and low computational burden, have been extensively investigated in data analysis field. But …
Fed-STWave: A Privacy-Preserving Federated Taxi Demand Prediction Model
M Zhang, W Li - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
With the proliferation of big data and advancements in intelligent transportation, taxi services
have emerged as one of the primary commuting modes, resulting in a substantial influx of …
have emerged as one of the primary commuting modes, resulting in a substantial influx of …
Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting
Accurate spatial-temporal traffic flow forecasting is crucial in aiding traffic managers in
implementing control measures and assisting drivers in selecting optimal travel routes …
implementing control measures and assisting drivers in selecting optimal travel routes …
Challenges and opportunities in traffic flow prediction: review of machine learning and deep learning perspectives
SAU Gilani, M Al-Rajab, M Bakka - Data and Metadata, 2024 - dm.ageditor.ar
In recent days, traffic prediction has been essential for modern transportation networks.
Smart cities rely on traffic management and prediction systems. This study utilizes state-of …
Smart cities rely on traffic management and prediction systems. This study utilizes state-of …