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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| 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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