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Unraveling the Winds of Change: Machine Learning Based Analysis and Forecasting of Wind Power Generation at Senegal's Taiba N'Diaye Wind Farm

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

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Practical Business Statistics

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Short-term wind speed prediction using Extended Kalman filter and machine learning

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Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network

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Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization

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A new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets

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An online-learning-enabled self-attention-based model for ultra-short-term wind power forecasting

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

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A probabilistic approach for short-term prediction of wind gust speed using ensemble learning

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Support vector machines for wind speed prediction

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A novel hybrid model based on STL decomposition and one-dimensional convolutional neural networks with positional encoding for significant wave height forecast

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Offshore wind speed assessment with statistical and attention-based neural network methods based on STL decomposition

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Short-Term Wind Speed Forecasting Based on Information of Neighboring Wind Farms

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Seasonal Analysis and Prediction of Wind Energy Using Random Forests and ARX Model Structures

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ARIMA-Based Frequency-Decomposed Modeling of Wind Speed Time Series

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Interval Deep Generative Neural Network for Wind Speed Forecasting

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Deep Concatenated Residual Network With Bidirectional LSTM for One-Hour-Ahead Wind Power Forecasting

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A Spatiotemporal Directed Graph Convolution Network for Ultra-Short-Term Wind Power Prediction

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Long Short-Term Memory

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A STL decomposition-based deep neural networks for offshore wind speed forecasting

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RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series

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