Curve Fitting of Excitation Characteristics Based on Particle SwarmOptimizationLeast Squares Support Vector Machine Algorithm
DOI:
Author:
Affiliation:
(School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)
Fund Project:
Article
|
Figures
|
Metrics
|
Reference
|
Related
|
Cited by
|
Materials
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 PSOLSSVM 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 PSOLSSVM algorithm has high fitting accuracy.
Reference
Related
Cited by
Get Citation
WANG Juan, LIU Mingguang. Curve Fitting of Excitation Characteristics Based on Particle SwarmOptimizationLeast Squares Support Vector Machine Algorithm[J]. Electric Machines & Control Application,2017,44(7):26-29.