电机与控制应用2017，Vol.44Issue(7)：26-29,4.
基于粒子群算法-最小二乘支持向量机算法的磁化曲线拟合
Curve Fitting of Excitation Characteristics Based on Particle Swarm Optimization-Least Squares Support Vector Machine Algorithm
摘要
Abstract
Magnetization curve was strongly nonlinear function.It was important to improve the accuracy of the magnetization curve fitting for the model of electrical equipment containing ferromagnetic material.Therefore,a method of magnetization curve fitting based on PSO-LSSVM algorithm was proposed.The method used particle swarm optimization algorithm to solve the LSSVM parameters selection problem.The simulation results showed that PSOLSSVM algorithm could obtain optimal LSSVM parameters and the magnetization curve used PS0-LSSVM algorithm has high fitting accuracy.关键词
磁化曲线/最小二乘支持向量机/粒子群算法/曲线拟合/参数优化Key words
magnetization curve/least squares support vector machine (LSSVM)/particle swarm optimization (PSO)/curve fitting/parameter optimization分类
信息技术与安全科学引用本文复制引用
王娟,刘明光..基于粒子群算法-最小二乘支持向量机算法的磁化曲线拟合[J].电机与控制应用,2017,44(7):26-29,4.基金项目
中央高校基本科研业务费专项资金资助项目(2015JBM085) （2015JBM085）
