By the improved BP and RBF neural networks, short-term electric load is forecast and training (convergence) rate and forecasting precision are analyzed.

利用改进的BP网络和RBF网络进行了短期电力负荷预测，并对训练的收敛速度和预测精度进行了分析。

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Calculating results show that the parameter optimization method can improve the precision of the satellite clock error short-term predicating.

计算结果表明，参数优化法可以提高卫星钟差短期预报的精度。

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Therefore, how to improve the forecasting precision is the emphasis on the study of short-term load forecasting.

因此，关于如何提高预测精度的问题，一直是短期负荷预测研究的重点问题。

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