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

WANG Tao-sheng(王涛生)^{1, 2}, ZUO Hong-yan(左红艳)^{1, 3}

(1. Research Center of Engineering Technology for Engineering Vehicle Chassis Manufacturing of
Hunan Province, Changsha 410205, China;
2. Research Base of Multinational Investment and Operations in Hunan Province, Changsha 410205, China;
3. School of Resource and Safety Engineering, Central South University, Changsha 410083, China)

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%.

Key words:chaos; immune algorithm; fuzzy; support vector machine