Short-Term Wind Speed or Power Forecasting With Heteroscedastic Support Vector Regression

By Qinghua Hu, Shiguang Zhang, Man Yu, Zongxia Xie. IEEE Transactions on Sustainable Energy, 2016

147 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/71f21c29772f48bcfbcddd870eb4c96506ed0494

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1. Jianhui Wang
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Citations in the corpus

• Spatio-Temporal Graph Deep Neural Network for Short-Term Wind Speed Forecasting (2019, methodology): “In [16], an optimal loss function is derived for heteroscedastic regression, and a novel SVR framework is developed for short-term wind forecasting based on learning tasks of Gaussian noise with heteroscedasticity.”