Abstract A new mathematical modeling method named support vector machine(SVM) model for permanent magnet spherical motors is presented. Three parameter optimization algorithms based on grid search, genetic algorithm(GA) and particle swarm optimization(PSO) are used respectively. The parameters obtained by three algorithms are analyzed and compared, and the algorithm which most fits the SVM model of permanent magnet spherical motor is confirmed.
Ju Lufeng,Wang Qunjing,Li Guoli等. Parameter Optimization for Support Vector Machine Model of <br/>Permanent Magnet Spherical Motors[J]. Transactions of China Electrotechnical Society, 2014, 29(1): 85-90.
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