提出了一类新的用于非线性时间序列建模的混合自回归滑动平均模型。
We obtain some results as follows:In chapter 2, a new mixture autoregressive moving average model is proposed for modeling nonlinear time series.
提出了一类用于非线性时间序列建模的混合自回归滑动平均模型(MARMA)。
A mixed autoregressive moving average (MARMA) model is proposed for modeling nonlinear time series.
用支持向量回归（SVR）的方法分析和预测时间序列，可解决复杂非线性系统的建模问题。
The Support Vector Regression(SVR)is used for the time series analysis and prediction to resolve the complex nonlinear system modeling problems.
RBF网络对非线性时间序列具有很高的建模精度；
RBF network can model nonlinear time series with high precision;
RBF网络对非线性时间序列具有很高的建模精度；
RBF network can model nonlinear time series with high precision;
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