Adaptive Particle Swarm Optimization Based on Kernel Support Vector Machine for Optimal Design of Synchronous Reluctance Motor.

This paper proposes an adaptive particle swarm optimization (APSO) based on a kernel support vector machine (KSVM). The proposed algorithm improves the convergence speed and exploration capability of the APSO by employing an individual adaptive parameter control based on the KSVM. To verify the algorithm’s effectiveness, it was compared with both the conventional PSO and APSO based on test functions. Finally, we applied the proposed algorithm to the optimal design of a synchronous reluctance motor (Syn-RM). [ABSTRACT FROM AUTHOR]