Application of data twinning based on deep time series model in smart city traffic flow prediction
Abstract This paper introduces an intelligent traffic flow prediction system that combines data twinning and deep learning, aiming to improve the prediction accuracy and model adaptability by integrating grey prediction model (GM(1,1)), long-short-term memory network (LSTM) and particle swarm optimi...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-05-01
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| Series: | Discover Internet of Things |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s43926-025-00144-2 |
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