关键词: 布谷鸟搜索, 支持向量机, 参数优化, 分类评估

Abstract: This study puts forward an improved method based on multiple population parallel search and adaptive search step for a new type of intelligent evolutionary algorithm which is named the cuckoo search algorithm. Then it introduces the improved method to optimize the support vector machine parameters and the detailed program that how to use the improved cuckoo search algorithm to optimize the parameters is proposed and applied to evaluate the listed company’s financial risk. The results show that the improved method can effectively improve the classification performance to the quarterly financial data risk model. And the simulation results find that besides the high accuracy, the improved cuckoo search algorithm has faster convergence speed and stability compared to the original cuckoo search algorithm, genetic algorithm and particle swarm optimization.

Key words: cuckoo search, support vector machine, parameter optimization, classification evaluation