STN-GCN: Spatial and Temporal Normalization Graph Convolutional Neural Networks for Traffic Flow Forecasting

In recent years, traffic forecasting has gradually become a core component of smart cities. Due to the complex spatial-temporal correlation of traffic data, traffic flow prediction is highly challenging. Existing studies are mainly focused on graphical modeling of fixed road structures. However, thi...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Electronics (Basel) 2023-07, Vol.12 (14), p.3158
Hauptverfasser:	Wang, Chunzhi, Wang, Lu, Wei, Siwei, Sun, Yun, Liu, Bowen, Yan, Lingyu
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Artificial neural networks Deep learning Feature extraction Forecasting Graph neural networks Graphs Learning Machine learning Mathematical models Minima Modelling Modules Neural networks Public transportation Spatial dependencies Statistical methods Time series Traffic flow Traffic information
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!