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- W2356559500 abstract "In order to improve the accuracy of wind power prediction and reduce the difficulty of power grid dispatching,this article analyzes the factors that influence wind power prediction such as wind speed,wind direction,wind power and temperature,studies the method of wind power prediction, and proposes short-term wind power prediction method based on multiple variable inputs wavelet-neural network.By comparing the single variable input with multiple variable inputs,it demonstrates that prediction accuracy between BP neural network and wavelet-neural network is different.And,in the same method,the number of input variables also impact on the prediction accuracy.Through the final comparative study,the conclusion is that to predict wind electricity power based on multiple variable inputs wavelet-neural network can improve prediction accuracy." @default.
- W2356559500 created "2016-06-24" @default.
- W2356559500 creator A5083839930 @default.
- W2356559500 date "2011-01-01" @default.
- W2356559500 modified "2023-09-26" @default.
- W2356559500 title "Forecasting Research on Short-term Wind Electricity Power Based on Wavelet-neural Network" @default.
- W2356559500 hasPublicationYear "2011" @default.
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