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Research on the Short-term Agricultural Electric Load Forecasting of Wavelet Neural Network

机译:小波神经网络短期农业电力负荷预测研究

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This paper proposes a new method for load forecasting—the wavelet neural network model for daily load forecasting. The neural call function is basis of nonlinear wavelets. A wavelet network is composed by the wavelet basis function. The global optimum solution is got. We overcome the intrinsic defects of a artificial neural network that its learning speed is slow, its network structure is difficult to determine rationally and it produces local minimum points. It can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the daily agricultural electric load forecasting.
机译:本文提出了一种对日常负荷预测的负载预测 - 小波神经网络模型的新方法。神经呼叫功能是非线性小波的基础。小波网络由小波基函数组成。 GOT全球最佳解决方案。我们克服了人工神经网络的内在缺陷,即其学习速度速度很大,其网络结构难以合理地确定,并且它产生局部最小点。从该方法可以看出,该方法可以有效地提高预测精度和速度。它可以应用于日常农业负荷预测。

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