A multi-Layer CNN-GRUSKIP model based on transformer for spatial −TEMPORAL traffic flow prediction

Traffic flow prediction remains a cornerstone for intelligent transportation systems (ITS), influencing both route optimization and environmental efforts. While Recurrent Neural Networks (RNN) and traditional Convolutional Neural Networks (CNN) offer some insights into the spatial–temporal dynamics...

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Bibliographic Details
Main Authors:	Karimeh Ibrahim Mohammad Ata, Mohd Khair Hassan, Ayad Ghany Ismaeel, Syed Abdul Rahman Al-Haddad, Thamer‎ Alquthami, Sameer Alani
Format:	Article
Language:	English
Published:	Elsevier 2024-12-01
Series:	Ain Shams Engineering Journal
Subjects:	Traffic Flow Prediction Convolutional Neural Network GRU Skip Function Transformer Spatial-temporal prediction
Online Access:	http://www.sciencedirect.com/science/article/pii/S2090447924004209
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A multi-Layer CNN-GRUSKIP model based on transformer for spatial −TEMPORAL traffic flow prediction

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