most citedImproving the Accuracy and Interpretability of Neural Networks for Wind Power Forecasting

3 citations · 7 across the 3 of their papers we have counts for

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cs.LG2023★ 2 cited

Explainable Modeling for Wind Power Forecasting: A Glass-Box Approach with High Accuracy

Wenlong Liao, Fernando Porte-Agel, Jiannong Fang +3

Machine learning models (e.g., neural networks) achieve high accuracy in wind power forecasting, but they are usually regarded as black boxes that lack interpretability. To address…

cs.LG2021

A Review of Graph Neural Networks and Their Applications in Power Systems

Wenlong Liao, Birgitte Bak-Jensen, Jayakrishnan Radhakrishna Pillai +2

Deep neural networks have revolutionized many machine learning tasks in power systems, ranging from pattern recognition to signal processing. The data in these tasks is typically r…