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A Novel Wind Power Forecasting Based Feature Selection and Hybrid Forecast Engine Bundled with Honey Bee Mating Optimization

机译:基于新型风力预测的特征选择和蜂窝交配优化捆绑的混合预测引擎

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In this study, new forecasting approach is developed for wind power signal based on Empirical Mode Decomposition (EMD), feature selection and forecast engine. Due to high volatility of wind power signal, we used a complex prediction approach with hybrid forecast engine. The proposed forecast engine is coupled with an intelligent algorithm to improve the training mechanism and optimize free parameters. To show the abilities of proposed forecasting approach real test case is considered by comparison with other strategies. In order to proof the superiority of suggested method, it is compared with various prediction approaches. Generated results confirm the validity of this strategy.
机译:在这项研究中,基于经验模式分解(EMD),特征选择和预测引擎的风电信号开发了新的预测方法。由于风电信号的高波动性,我们使用了一种具有混合预测引擎的复杂预测方法。所提出的预测引擎与智能算法耦合,以改善训练机制并优化自由参数。为了表明所提出的预测方法的能力,通过与其他策略进行比较,考虑了真正的测试案例。为了证明建议方法的优越性,将其与各种预测方法进行比较。生成的结果证实了这一战略的有效性。

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