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Multi-Task Autoencoders and Transfer Learning for Day-Ahead Wind and Photovoltaic Power Forecasts

, and . Energies, 15 (21): 8062 (2022)
DOI: 10.3390/en15218062

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Quantile Surfaces -- Generalizing Quantile Regression to Multivariate Targets, , , , and . arXiv e-prints, (2020)Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models., , and . GI-Jahrestagung, volume P-294 of LNI, page 585-598. GI, (2019)Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic., , and . ICANN (3), volume 11729 of Lecture Notes in Computer Science, page 550-564. Springer, (2019)Extended Coopetitive Soft Gating Ensemble, , , and . arXiv e-prints, (2020)Testing COP-Solvers with a Hyper-Redundant Manipulator Model. (July 2012)Emerging Relation Network and Task Embedding for Multi-Task Regression Problems, and . International Conference on Pattern Recognition (ICPR), page 2663--2670. IEEE, (2021)Transfer Learning in the Field of Renewable Energies -- A Transfer Learning Framework Providing Power Forecasts Throughout the Lifecycle of Wind Farms After Initial Connection to the Electrical Grid. Organic Computing -- Doctoral Dissertation Colloquium 2018, kassel university press, Kassel, Germany, (2019)Multi-Task Autoencoders and Transfer Learning for Day-Ahead Wind and Photovoltaic Power Forecasts, and . Energies, 15 (21): 8062 (2022)Representation Learning in Power Time Series Forecasting, , and . Deep Learning: Algorithms and Applications, Springer, (2020)Model selection, adaptation, and combination for transfer learning in wind and photovoltaic power forecasts, and . Energy and AI, (2023)