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Sep 17, 2023 · Our results suggest that the conformal based methods, with the pre-trained underlying model, produce slightly more conservative but more efficient probability ...
[PDF] Evaluation of conformal-based probabilistic forecasting methods ...
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Our work should be viewed as an introduction to how Conformal. Prediction methods can be used in the area of probabilistic wind forecasting. In section. 2 we ...
We apply Conformal Predictive Distribution Systems (CPDS) and a non-exchangeable version of the traditional Conformal Prediction (NECP) method to short-term ...
Evaluation of conformal-based probabilistic forecasting methods for short-term wind speed forecasting. In: H. Papadopoulos, K. A. Nguyen, Henrik Boström, L ...
Jul 3, 2023 · One such method, Conformal Prediction, shows a lot of promise for producing reliable probabilistic forecasts for wind. These forecasts take the ...
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Feb 1, 2024 · This paper proposes a non-crossing multi-output quantile regression deep neural network optimized by chaotic particle swarm optimization.
This study proposes a probabilistic forecasting method for short-term wind speeds based on the Gaussian mixture model and long short-term memory.
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Evaluation of conformal-based probabilistic forecasting methods for short-term wind speed forecasting · Decision Theory via Model-Free Generalized Fiducial ...
May 1, 2024 · This work proposes a day-ahead regional wind power forecasting framework using deep Convolutional Neural Networks (CNN) with context-aware turbine maps.
Jun 26, 2023 · The pur- pose of this report is to do an initial analysis of the effectiveness of conformal prediction methods to day ahead probabilistic wind ...