摘要
人工免疫系统是基于生物免疫系统特性而发展的新兴智能系统,本文介绍了人工免疫系统中的克隆选择原理。免疫克隆算法的参数设置通常是依靠经验和试验来确定,造成试验工作量大且难以得到最优的参数组合,影响了算法的使用。通过将免疫算法基本模型的参数设定问题描述成均匀设计中多因素、多水平的试验设计,从而能够用较少的试验很快设定算法参数的取值。仿真试验表明了该方法的可行性和有效性。
An artificial immune system is a novel intelligent system based on the characteristics of biological immune systems. The clonal selection principle in artificial immune systems is introduced. In general the parameters of an immune clonal algorithm are determined by experience and experiments. This leads to heavy work load and makes the optimal combination of the parameters difficult to obtain. A uniform design method is used to convert the problem of parameter establishment into the experimental design of multiple factors and multiple levels, and reduces the work load of determining the parameter values based on less experiments. The method applied to the benchmark problems shows good performance feasibility and effectiveness.
出处
《计算机工程与科学》
CSCD
2007年第10期35-37,共3页
Computer Engineering & Science
关键词
免疫算法
克隆选择
均匀设计
参数
immune algorithrn
clonal selection
uniform design
parameter
