On the basis of analysis of several methods for modeling, a soft sensor based on kernel principal component analysis (KPCA) and least square support vector machine (LSSVM) is proposed.
在具体分析了多种建模方法的基础上，提出了核主元分析结合最小二乘支持向量机软测量建模方法。
Several model building methods for the soft sensor are described, including regression analysis and neural networks.
探讨了软测量常用的几类建模方法，包括回归分析和神经网络。
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