基于粒子群优化模式搜索的支持向量机参数优化及应用

摘要

Considering the importance of selecting Kernel parameters, the Particle Swarm Optimization (PSO) model search algorithm was proposed to search optimal parameters. This method combined the global search capability of PSO algorithm and the good local convergence of mode search, that making PSO model search algorithm displays higher performance, and applied to an the practice of agricultural technological project classification. The results of experiment show that this method is not only efficient, but also catches the optimal parameters that have acTheved higher accuracy.%针对核函数参数选择的重要性,提出了粒子群(PSO)模式搜索算法来搜索最优参数,该算法结合了PSO算法的全局搜索能力强和模式搜索的局部收敛性好的优点,使PSO模式搜索算法表现出了较高的性能,并将其应用到农业科技项目分类中.实验结果表明,该算法不仅效率高,收敛速度快,而且搜索到的最优参数达到了较高的准确率.