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Exploring of Related Issues of BP Algorithm In Load Forecasting

机译:BP算法在负荷预测中相关问题的探讨。

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In this paper,the establishment of the neural network model of forecasting short-term power load in an electric power grid is studied.Basing on the model,the BP algorithm for power load is explored.The research on BP network model includes determining the hidden layer number,hidden layer nodes number,training frequency and accuracy of learning rate.In this paper,we focus on that how to give initial weights, select training sample method of normalizing sample and so on.With more further qualitative and quantitative analysis,and through an actual example as comparative test,we have got useful conclusions.
机译:本文研究了预测电网短期电力负荷的神经网络模型的建立。在此模型的基础上,探索了电力负荷的BP算法。BP网络模型的研究包括确定隐患。层数,隐层节点数,训练频率和学习率的准确性。本文重点研究如何赋予初始权重,选择归一化样本的训练样本方法等。通过一个实际例子作为比较测试,我们得出了有益的结论。

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