Parameter Selection of Support Vector Regression Machine Based on Differential Evolution Algorithm

This parameters selection is an important issue in the research of ¿-support vector regression machine (¿-SVRM), whose nature is an optimization selection process. Motivated by the effectiveness of differential evolution (DE) algorithm on optimization problem, a new automatic searching method based on DE algorithm was proposed. Experimental results demonstrate that ¿-SVRM model optimization based on DE algorithm has better prediction capability compared with the methods based on genetic algorithm (GA), ant colony optimization (ACO) and particle swarm optimization (PSO).