The Application of Entropy Method in Wind Power Combined Prediction
| Autor: | Kang Ping Li |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Engineering
Wind power Artificial neural network business.industry Mean squared prediction error General Medicine computer.software_genre Support vector machine Information fusion Radial basis function neural Entropy (information theory) Data mining business Algorithm computer Physics::Atmospheric and Oceanic Physics Combined method |
| Zdroj: | Applied Mechanics and Materials. :3043-3046 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.602-605.3043 |
| Popis: | A new combined method of wind power prediction based on entropy method is proposed according to information fusion technique. Firstly, Carry out the wind-power forecast with BP neural network, radial basis function neural network and support vector machine respectively. Then, weights of combination forecasting can be obtained according to the degree of variation of prediction error sequence. Case study was carried out to investigate the validity of the novel algorithm and the results illustrated that the proposed combined model can improve the short term forecasting accuracy of wind power effectively by tracking the change of wind power. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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