A modeling method for nonlinear dynamic system based on Support Vector Regression (SVR) was proposed in this paper.
提出一种基于支持向量回归机(SVR)的非线性动态系统建模方法。
First, a cascade model with neural networks and linear dynamic systems, which is determinate and general, is used in modeling the nonlinear dynamic systems.
首先用一种人工神经网络和线性动态系统的串级模型对非线性动态系统建模，这种模型具有很大的确定性与通用性。
The modeling results show that the nonlinear dynamic models are more accurate than the linear dynamic models to describe the sensor characteristics.
建模结果表明，动态非线性模型比线性模型更为准确地描述了热膜(线)式空气质量流量传感器的动态特性。
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