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Short-Term Wind Speed Forecast Based on Best Wavelet Tree Decomposition and Support Vector Machine Regression

机译:基于最佳小波树分解和支持向量机回归的短期风速预测

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Wind power industry developed rapidly in recent years, wind power is a type of power with randomness and fluctuation. Accurate wind speed forecasting can reduce the impact of wind power. Paper analyzed the wind speed signal with wavelet packet decomposition method from low-frequency and high-frequency, selected the optimal wavelet tree through the principle of minimum entropy. Short-term wind speed prediction model is built with support vector machine regression. This algorithm has advanced and better accuracy by comparing the results.
机译:近年来,风电产业发展迅速,风电是一种具有随机性和波动性的电力。准确的风速预测可以减少风能的影响。本文采用小波包分解的方法从低频和高频分析风速信号,并通过最小熵原理选择了最优的小波树。利用支持向量机回归建立了短期风速预测模型。通过比较结果,该算法具有更高的精度。

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