81 citations · 93 across the 7 of their papers we have counts for
3 papers · 1 filter
Improving the Accuracy and Interpretability of Neural Networks for Wind Power Forecasting
Wenlong Liao, Fernando Porte-Agel, Jiannong Fang +3
Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their f…
An Explainable Framework for Machine learning-Based Reactive Power Optimization of Distribution Network
Wenlong Liao, Benjamin Schäfer, Dalin Qin +3
To reduce the heavy computational burden of reactive power optimization of distribution networks, machine learning models are receiving increasing attention. However, most machine…
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…