【作者】 邓九英； 毛宗源；

【Author】 Deng Jiuying1,2,Mao Zongyuan2 1.Department of Computer Science,Guangdong Institute of Education,Guangzhou 510303,P.R.China2.College of Automatic Science & Engineering,South China University of TechnologyM Guangzhou 510641,P.R.China

【机构】 广东教育学院计算机科学系； 华南理工大学自动化科学与工程学院；

【摘要】 根据人工免疫网络的多峰函数优化方法,利用混沌映射的随机性和各态遍历性,以及混沌吸引子方程中变量渐进稳定到平衡点的特性,提出一种新的混合多峰函数优化算法,能够加速优化解的搜索,提高优化解的精确度,大大改进了免疫网络多峰函数优化算法(opt-aiNet)对输入参数的敏感性.对实例进行优化测试,优化结果显示了混合算法的通用性、高效性与精确性。更多还原

【Abstract】 After the immune network algorithms of multi-modal function optimization have developed,their performance can be improved by stochastic chaos map.In chaos attractor equations the variables are steadily approached stable points.A novel algorithm of immune network combined chaos is presented.The solutions searched and optimized can be accelerated using this method.According to opt-aiNet improved,parameters sensitivity can be bated.At last,some functions are tested.Through multi-peak illustrated and results optimized,the approach is verified with high generalized,efficiency and precision.更多还原