A Hybrid Deep Convolutional Neural Network Approach for Predicting the Traffic Congestion Index

A Hybrid Deep Convolutional Neural Network Approach for Predicting the Traffic Congestion Index

Traffic congestion is one of the most important issues in large cities, and the overall travel speed is an important factor that reflects the traffic status on road networks. This study proposes a hybrid deep convolutional neural network (CNN) method that uses gradient descent optimization algorithm...

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Bibliographic Details
Main Authors: Duy Tran Quang, Sang Hoon Bae
Format: Article
Language:English
Published: University of Zagreb, Faculty of Transport and Traffic Sciences 2021-05-01
Series:Promet (Zagreb)
Subjects:
traffic congestion prediction
deep learning
convolutional neural network
probe vehicles
gradient descent optimization
Online Access:https://traffic.fpz.hr/index.php/PROMTT/article/view/3657

Internet

https://traffic.fpz.hr/index.php/PROMTT/article/view/3657

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