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Energy forecasting with robust, flexible, and explainable machine learning algorithms.

, , , , , , , , , , , , , , и . AI Mag., 44 (4): 377-393 (декабря 2023)

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Ziqing Ou

Yuzhao Ma

Characterization of higher order modes in optical fibers. Uni Erlangen-Nürnberg, (2009)

Jingxiang Ma

Tsie Ma

Lan Ma

 

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Hybrid Attention Networks for Flow and Pressure Forecasting in Water Distribution Systems., , , и . CoRR, (2020)GCformer: An Efficient Solution for Accurate and Scalable Long-Term Multivariate Time Series Forecasting., , , , , и . CIKM, стр. 3464-3473. ACM, (2023)SADI: A Self-Adaptive Decomposed Interpretable Framework for Electric Load Forecasting Under Extreme Events., , , , , , , и . ICASSP, стр. 1-5. IEEE, (2023)FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting., , , , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 27268-27286. PMLR, (2022)Energy forecasting with robust, flexible, and explainable machine learning algorithms., , , , , , , , , и 5 other автор(ы). AI Mag., 44 (4): 377-393 (декабря 2023)TreeDRNet: A Robust Deep Model for Long Term Time Series Forecasting., , , , , , и . CoRR, (2022)GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting., , , , , и . CoRR, (2023)Transformers in Time Series: A Survey., , , , , , и . CoRR, (2022)Transformers in Time Series: A Survey, , , , , , , и . arxiv, (2023)FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting., , , , , , и . CoRR, (2024)