Immunodomaince Based Clonal Selection Clustering Algorithm

Based on clonal selection principle and the immunodominance theory,a new immune clustering algorithm,Immunodomaince based Clonal Selection Clustering Algorithm(IDCSCA) is proposed in this paper.An immunodomaince operator is introduced to the clonal selection algorithm,which can realize on-line gaining priori knowledge and sharing information among different individuals.Firstly,the gene of elites in antibody population can be extracted and generalized to ordinary antibodies,by the interaction,the whole antibody population evolves.The proposed method has been extensively compared with Fuzzy C-means(FCM),Genetic Algorithm based FCM(GAFCM) and Clonal Selection Algorithm based FCM(CSAFCM) over a test suit of several real life data sets and synthetic data sets.The result of experiment indicates the superiority of the IDCSCA over FCM,GAFCM and CSAFCM on stability and reliability for its ability to avoid trapping in local optimum.