Traffic flow prediction based on spatiotemporal encoder-decoder model.

Traffic flow prediction based on spatiotemporal encoder-decoder model.

To more effectively capture the periodic and dynamic changes in urban traffic flow and the spatiotemporal correlation of complex road networks, a new traffic flow prediction method, the Enhanced Spatiotemporal Graph Convolutional Network Encoder-Decoder Model (ESGCN-EDM), is proposed. The model achi...

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Bibliographic Details
Main Authors: Yuanming Ding, Wei Zhao, Lin Song, Chen Jiang, Yunrui Tao
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0321858
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