Multi Long-Short Term Memory Models for Short Term Traffic Flow Prediction

Multi Long-Short Term Memory Models for Short Term Traffic Flow Prediction

Many single model methods have been applied to real-time short-term traffic flow prediction. However, since traffic flow data is mixed with a variety of ingredients, the performance of single model is limited. Therefore, we proposed Multi-Long-Short Term Memory Models, which improved traffic flow pr...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEICE Transactions on Information and Systems 2018/12/01, Vol.E101.D(12), pp.3272-3275
Hauptverfasser: XUE, Zelong, XUE, Yang
Format: Artikel
Sprache:eng
Schlagworte:
k-means clustering
Model accuracy
multi-lstm models
Short term
short term traffic flow prediction
Traffic flow
Traffic models
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Many single model methods have been applied to real-time short-term traffic flow prediction. However, since traffic flow data is mixed with a variety of ingredients, the performance of single model is limited. Therefore, we proposed Multi-Long-Short Term Memory Models, which improved traffic flow prediction accuracy comparing with state-of-the-art models.
ISSN:0916-8532
1745-1361
DOI:10.1587/transinf.2018EDL8087