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Soft sensor modeling based on support vector machine

Feng Rui
TLDR
A soft sensor model based on the SVM that features high learning speed, good approximation, well generalization ability, and little dependence on the sample set is presented.
Abstract
Support vector machine (SVM) is a new learning machine based on the statistical learning theory. This paper presents a soft sensor model based on the SVM. Theoretical and simulation analysis indicates that this method features high learning speed, good approximation, well generalization ability, and little dependence on the sample set. It has the better performance than the soft sensor modeling based on the RBF neural network.

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Book ChapterDOI

RBF Kernel Based Support Vector Machine with Universal Approximation and Its Application

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