A new wind power prediction method based on ridgelet transforms, hybrid feature selection and closed-loop forecasting
Top Cited Papers
- 1 April 2018
- journal article
- research article
- Published by Elsevier BV in Advanced Engineering Informatics
- Vol. 36, 20-30
- https://doi.org/10.1016/j.aei.2018.02.006
Abstract
No abstract availableKeywords
This publication has 36 references indexed in Scilit:
- A holistic approach for the cognitive control of production systemsAdvanced Engineering Informatics, 2010
- Management and forecast of dynamic customer needs: An artificial immune and neural system approachAdvanced Engineering Informatics, 2010
- A review on the forecasting of wind speed and generated powerRenewable and Sustainable Energy Reviews, 2009
- Incorporating power system security into market‐clearing of day‐ahead joint energy and reserves auctionsEuropean Transactions on Electrical Power, 2008
- Emergent short-term forecasting through ant colony engineering in coordination and control systemsAdvanced Engineering Informatics, 2006
- Long-Term Wind Speed and Power Forecasting Using Local Recurrent Neural Network ModelsIEEE Transactions on Energy Conversion, 2006
- Standardizing the Performance Evaluation of Short-Term Wind Power Prediction ModelsWind Engineering, 2005
- Comparison among five evolutionary-based optimization algorithmsAdvanced Engineering Informatics, 2005
- Estimating mutual informationPhysical Review E, 2004
- Using mutual information for selecting features in supervised neural net learningIEEE Transactions on Neural Networks, 1994