Cross-City Multi-Granular Adaptive Transfer Learning for Traffic Flow Prediction

Accurate traffic prediction is one of the most important techniques in building a smart city. Many works, especially deep learning models, have made great progress in traffic prediction based on rich historical data. However, many cities still suffer from the problem of data scarcity in many aspects...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2023-11, Vol.35 (11), p.1-12
Hauptverfasser:	Mo, Jiqian, Gong, Zhiguo
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Algorithms attention Cities Deep learning Encoding Feature extraction Machine learning meta-learning Predictive models Traffic flow traffic flow prediction Transfer learning Urban areas
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!