一种基于多智能体策略的人工免疫网络数据分类方法

摘要

在传统的人工免疫网络基础上，将多智能体技术的典型策略融入到免疫网络的进化过程中。算法引入了邻域克隆选择，操作过程从局部到整体，能够更加全面地模拟免疫网络的自然进化模型；同时在免疫网络进化过程中增加了抗体间的竞争和协作操作，提高了网络的动态分析能力。后续实验中，分别采用常用的三组UCI数据和一幅红树林多光谱TM遥感图像对算法加以验证，实验结果表明算法对遥感图像有较高的分类效率，对UCI数据也有较好的分类效果，表明该算法是一种有效的数据分类方法。%On the basis of the traditional artificial immune network,this paper integrated typical strategies of the multi-agent technology into the evolution of the immune network.It introduced the neighborhood clone selection into the algorithm,made the process of operation from local to the whole,which could simulate the natural evolution model of the immune network more comprehensive.In addition the neighborhood competition and neighborhood collaborative operators between the antibody were introduced into the evolution process of the immune network,which could improve the dynamic analysis capabiility of the net-work.Classification experiments used the UCI data mangrove multispectral TM images,experiment result shows that the algo-rithm has good classification efficiency for remote sensing image,UCI data also get a good result.Results show that the algo-rithm is an effective classification algorithm.