Adaptive chaos clonal evolutionary programming algorithm

作     者：DU Haifeng GONG Maoguo LIU Ruochen JIAO Licheng 

作者机构：Institute of Intelligent Information Processing and Key Laboratory of Radar Signal Processing XidianUniversity Xi'an 710071 China School of Mechanical Engineering Xi'an Jiaotong University Xi'an 710049 China 

出 版 物：《Science in China(Series F)》 (中国科学（F辑英文版）)

年 卷 期：2005年第48卷第5期

页      面：579-595页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 08[工学] 09[农学] 071007[理学-遗传学] 0901[农学-作物学] 0836[工学-生物工程] 090102[农学-作物遗传育种] 

基　　金：the National Natural Science Foundation of China(Grant Nos 60133010  60372045) 

主　　题：chaos clonal selection evolutionary algorithms 

摘      要：Based on the chaos movement and the clonal selection theory, a novel artificial immune system algorithm, Adaptive Chaos Clonal Evolutionary Programming Algorithm （ACCEP）, is proposed in this paper. The new algorithm uses the Logistic Sequence to control the mutation scale and uses the Chaos Mutation Operator to control the clonal selection. Compared with SGA and Clonal Selection Algorithm, ACCEP can enhance the precision and stability, avoid prematurity to some extent, and have the high convergence speed. The results of the experiment indicate that ACCEP has the capability to solve complex machine learning tasks, like Multimodal Function Optimization.