title: A dynamic clonal selection immune clustering algorithm.
abstract: According to the basis of clonal selection immune algorithm and hierarchical clustering, a dynamic clonal selection immune clustering algorithm is presented, which no pre-knowledge is needed. The proposed algorithm bases on antibody affinity, to recognize antigen, restrain and merge antibody. By using aiNET immune network model, the algorithm mutates location of antibodies, in which the mutating rate is dynamically adjusted with inverse proportion to the number of immune evolution generations. After dynamic mutation, the similar antibodies are merged again, and the same processes repeats until it meets the ending condition. Experimental results showed that the proposed algorithm is more coincidental reality of clustering and more preferable performance than traditional ones.
authors.affiliation: Shantou University Medical College, Shantou 515041, China. ywchen@stu.edu.cn
authors.forename: Yao-wen
authors.initials: YW
authors.lastname: Chen
authors.forename: Lin
authors.initials: L
authors.lastname: Huang
authors.forename: Wei-ming
authors.initials: WM
authors.lastname: Luo
authors.forename: Jing-xia
authors.initials: JX
authors.lastname: Huang
authors.forename: Ren-hua
authors.initials: RH
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D032701:Biomimetics / Q000379:methods*; D019976:Cloning, Organism; D016000:Cluster Analysis; D008957:Models, Genetic; D018448:Models, Immunological; D012641:Selection, Genetic