A Hybrid Method for Traffic Flow Forecasting Using Multimodal Deep Learning

Traffic flow forecasting has been regarded as a key problem of intelligent transport systems. In this work, we propose a hybrid multimodal deep learning method for short-term traffic flow forecasting, which can jointly and adaptively learn the spatial–temporal correlation features and long temporal...

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Bibliographic Details
Main Authors: Shengdong Du, Tianrui Li, Xun Gong, Shi-Jinn Horng
Format: Article
Language:English
Published: Atlantis Press 2020-01-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Online Access:https://www.atlantis-press.com/article/125932622/view