An Immune Network Algorithm with Density and Depth Information for Data Clustering

摘要：

AINet is an evolutionary algorithm based on the principle of immune system.In this paper,we introduce a noveI algorithm AlNDD (AINet with Density and Depth factor)which is implemented by modifying AINet with two factors that is absent in the original algorithm.We apply this algorithm in data clustering to illustrate the main process.There are basically two steps taken.First,the experimental data set is compressed bv AINet with the density factor which is designed to ameliorate the antibody mutated effect.Then the multilayer MST cutting strategY with a depth factor is operated on the output of the first step.The obtained clustering results show that this algorithm can increase the accuracy of data clustering on some level.which could shed some Iights on the further improvements of artificial immunenetwork models.

作者: Lin Fan Xu Jiayi

会议类型: 国际会议

会议名称: The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)

会议地点: 成都

会议语种:英文

页码: 196-199

在线出版日期: 2007-12-19（万方平台首次上网日期，不代表论文的发表时间）