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Probabilistic Wind Power Forecasting via Non-Stationary Gaussian Processes

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.apenergy.2013.03.038openalex-extracted

Sparse online warped Gaussian process for wind power probabilistic forecasting

inferredcites →https://doi.org/10.1016/j.egyr.2020.06.018openalex-extracted

Gaussian process power curve models incorporating wind turbine operational variables

inferredcites →https://doi.org/10.1016/j.egyr.2022.11.202openalex-extracted

Short-term wind power forecasting and uncertainty analysis based on FCM–WOA–ELM–GMM

inferredcites →https://doi.org/10.1016/j.isatra.2022.07.028openalex-extracted

Priori-guided and data-driven hybrid model for wind power forecasting

inferredcites →https://doi.org/10.1016/j.renene.2019.09.145openalex-extracted

Probabilistic modelling of wind turbine power curves with application of heteroscedastic Gaussian Process regression

inferredcites →https://doi.org/10.1109/tai.2021.3128368openalex-extracted

WindGMMN: Scenario Forecasting for Wind Power Using Generative Moment Matching Networks

inferredcites →https://doi.org/10.1109/tia.2021.3086077openalex-extracted

A Regional Wind Power Probabilistic Forecast Method Based on Deep Quantile Regression

inferredcites →https://doi.org/10.1109/tpwrs.2013.2282366openalex-extracted

Wind Power Forecasts Using Gaussian Processes and Numerical Weather Prediction

inferredcites →https://doi.org/10.1109/tpwrs.2020.2971607openalex-extracted

Improved Deep Mixture Density Network for Regional Wind Power Probabilistic Forecasting

inferredcites →https://doi.org/10.1109/tste.2021.3086851openalex-extracted

Multi-Source and Temporal Attention Network for Probabilistic Wind Power Prediction

inferredcites →https://doi.org/10.1109/tste.2021.3124228openalex-extracted

Online Ensemble Approach for Probabilistic Wind Power Forecasting

inferredcites →https://doi.org/10.1515/9781400881994openalex-extracted

Lectures on Fourier Integrals. (AM-42)

inferredcites →https://doi.org/10.35833/mpce.2020.000849openalex-extracted

Spatio-temporal Convolutional Network Based Power Forecasting of Multiple Wind Farms

inferredcites →https://doi.org/10.35833/mpce.2020.000874openalex-extracted

Performance Improvement of Very Short-term Prediction Intervals for Regional Wind Power Based on Composite Conditional Nonlinear Quantile Regression

inferredcites →https://doi.org/10.35833/mpce.2021.000717openalex-extracted

Wind Power Prediction Based on Multi-class Autoregressive Moving Average Model with Logistic Function

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1109/ciml69155.2026.11692690openalex-snapshot

Wind Power Output Forecasting Based on an Improved LSTM Model

inferred← citeshttps://doi.org/10.1109/ic-eeta66496.2025.11548512openalex-snapshot

AI-Enabled Predictive Modelling of Wind Energy Output Using ML and DL Algorithms

inferred← citeshttps://doi.org/10.1109/icscss64956.2025.11501135openalex-snapshot

Spatiotemporal Hybrid Ensemble with Uncertainty Awareness for Short-Term Wind Power Forecasting

inferred← citeshttps://doi.org/10.3390/forecast8050093openalex-snapshot

Long-Term Wind Power Forecasting via a Hybrid Statistical–Stochastic–Machine Learning Approach

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