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Xuanbing Zhu, Tze‐Kuang Chen, Yingguang Hao
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10.3115/v1/d14-1179
10.3115/v1/d14-1179
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Enhancing road traffic flow prediction with improved deep learning using wavelet transforms
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A time series is worth 64 words: Long-term forecasting with transformers
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Effective attention model for global sea surface temperature prediction
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Electricity consumption forecasting for sustainable smart cities using machine learning methods
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Deep learning-based forecasting of electricity consumption
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Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
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Are transformers effective for time series forecasting?
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Deep learning-based forecasting of electricity consumption
10.1038/s41598-024-56602-4 · doi-reference
Electricity consumption forecasting for sustainable smart cities using machine learning methods
10.1016/j.iot.2024.101322 · doi-reference
A fundamental diagram based hybrid framework for traffic flow estimation and prediction by combining a markovian model with deep learning
10.1016/j.eswa.2023.122219 · doi-reference
Effective attention model for global sea surface temperature prediction
10.1016/j.eswa.2024.124411 · doi-reference
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
10.52202/079017-2196 · doi-reference
Non-stationary transformers: Exploring the stationarity in time series forecasting
10.52202/068431-0718 · doi-reference
SCINet: Time series modeling and forecasting with sample convolution and interaction
10.52202/068431-0421 · doi-reference
Enhancing road traffic flow prediction with improved deep learning using wavelet transforms
10.1016/j.rineng.2024.102342 · doi-reference
10.3115/v1/d14-1179
10.3115/v1/d14-1179 · doi-reference