Fuzzy least squares support vector machine soft measurement model based on adaptive mutative scale chaos immune algorithm

Tao-sheng Wang , Hong-yan Zuo

Journal of Central South University ›› 2014, Vol. 21 ›› Issue (2) : 593 -599.

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Journal of Central South University ›› 2014, Vol. 21 ›› Issue (2) : 593 -599. DOI: 10.1007/s11771-014-1978-4
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Fuzzy least squares support vector machine soft measurement model based on adaptive mutative scale chaos immune algorithm

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Abstract

In order to enhance measuring precision of the real complex electromechanical system, complex industrial system and complex ecological & management system with characteristics of multi-variable, non-liner, strong coupling and large time-delay, in terms of the fuzzy character of this real complex system, a fuzzy least squares support vector machine (FLS-SVM) soft measurement model was established and its parameters were optimized by using adaptive mutative scale chaos immune algorithm. The simulation results reveal that fuzzy least squares support vector machines soft measurement model is of better approximation accuracy and robustness. And application results show that the relative errors of the soft measurement model are less than 3.34%.

Keywords

chaos / immune algorithm / fuzzy / support vector machine

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Tao-sheng Wang, Hong-yan Zuo. Fuzzy least squares support vector machine soft measurement model based on adaptive mutative scale chaos immune algorithm. Journal of Central South University, 2014, 21(2): 593-599 DOI:10.1007/s11771-014-1978-4

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