High-performance traffic volume prediction: An evaluation of RNN, GRU, and CNN for accuracy and computational trade-offs

High-performance traffic volume prediction: An evaluation of RNN, GRU, and CNN for accuracy and computational trade-offs

Predicting urban traffic volume presents significant challenges due to complex temporal dependencies and fluctuations driven by environmental and situational factors. This study addresses these challenges by evaluating the effectiveness of three deep learning architectures— Recurrent Neural Network...

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Bibliographic Details
Main Authors: Pranolo Andri, Saifullah Shoffan, Bella Utama Agung, Wibawa Aji Prasetya, Bastian Muhammad, Hardiyanti P Cicin
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:BIO Web of Conferences
Online Access:https://www.bio-conferences.org/articles/bioconf/pdf/2024/67/bioconf_icobeaf2024_02034.pdf
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