在用AR、ARMA等线性模式对气候序列进行拟合和预报时，由于气候序列中存在着非线性变化，所以拟合和预报效果往往不太理想。

Using linear regressive models (e. g. AR, ARMA model) to fit and predict the climatic time series, the results are not sufficiently good because there exist nonlinear variations in the time series.

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本文用递归神经网络逼近非线性ARMA模型预测电力短期负荷。

The recursive neural network based nonlinear approaching ARMA model is adopted for short-term power load prediction in this paper.

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本文研究了结构非线性振动及其控制系统的ARMA模型的建立问题。

ARMA model of nonlinear structural vibration and control systems were studied in this paper.

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