Zhou, Yuxuan (2023) Temporal Fusion Transformers Model for Traffic Flow Prediction. In: Proceedings of the 2nd International Conference on Big Data Economy and Digital Management, BDEDM 2023, January 6-8, 2023, Changsha, China.
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Abstract
Temporal Fusion Transformers (TFT) is a Transformer model for multi-step forecasting tasks. Because TFT models can integrate decoders to import various types of inputs, including static covariates, known future inputs, and other exogenous time series observed only in the past, which are well perform
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 16:17 |
| Last Modified: | 17 Apr 2026 03:09 |
| URI: | http://eprints.eai.eu/id/eprint/43141 |
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