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Arxiv
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364
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Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series Forecasting
- Time series forecasting is important in various domains such as energy management and financial markets.
- The Times2D method transforms 1D time series into 2D space to capture complex temporal variations.
- It consists of a Periodic Decomposition Block, First and Second Derivative Heatmaps, and an Aggregation Forecasting Block.
- Times2D achieves state-of-the-art performance in both short-term and long-term forecasting.
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