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Research on A Genetic Neural Artificial Network in Short Term Load Forecasting

机译:遗传神经网络在短期负荷预测中的研究

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Short-term load forecasting is one of the most important contents of running and dispatching power system. In order to avoid the limitation of the BP neural networks and improve the efficiency and the accuracy of forecasting,this paper established the short-term load forecasting based on the Genetic Neural Artificial Network. The model mended the activation function ,introduced the momentim item and made use of GA to confirm the parameters of the networks. The example showed that this model can effectively improve the forecasting precision.
机译:短期负荷预测是电力系统运行和调度的最重要内容之一。为了避免BP神经网络的局限性,提高预测的效率和准确性,建立了基于遗传神经人工网络的短期负荷预测方法。该模型修正了激活函数,引入了矩项,并利用遗传算法来确定网络的参数。实例表明,该模型可以有效提高预测精度。

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