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RESEARCH ON THE SHORT-TERM AGRICULTURAL ELECTRIC LOAD FORECASTING OF WAVELET NEURAL NETWORK

机译:小波神经网络的短期农业电力负荷预测研究

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摘要

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:本文提出了一种负荷预测的新方法-小波神经网络模型进行负荷预测。神经调用函数是非线性小波的基础。小波网络由小波基函数组成。得到了全局最优解。我们克服了人工神经网络的内在缺陷,即学习速度慢,网络结构难以合理确定并产生局部最小值。从实例中可以看出,该方法可以有效提高预报的准确性和速度。可以应用于日常农业用电负荷预测。

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