Research on Artificial Immune Algorithm Based on Controllable Optimal Objectives

摘要：

We investigated several existing artificial immune models and there are not involve object controlled function and possess a memory network with dynamic change. The paper proposed a clustering algorithm of artificial immune network based on controllable optimal objectives. In the algorithm, the compression and clustering are abstracted as a multi-objective planning problem. The learning ability of immune system is improved by adopting the pool of memory cells strategy. The simulation of kernel clustering shows a satisfying result can be acquired by using the immune model with controllable optimal objectives.

关键词： artificial immune algorithm function optimization clustering data compression

作者: Tian Yuling Wang Fan

作者单位: Computer and software department Taiyuan University of technology Taiyuan, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 119-122

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）