A dynamic clonal selection immune clustering algorithm.
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.
Chen
Yao-wen
YW
Shantou University Medical College, Shantou 515041, China. ywchen@stu.edu.cn
Huang
Lin
L
Luo
Wei-ming
WM
Huang
Jing-xia
JX
Wu
Ren-hua
RH
D000465:Algorithms; D001185:Artificial Intelligence; D032701:Biomimetics / Q000379:methods*; D019976:Cloning, Organism; D016000:Cluster Analysis; D008957:Models, Genetic; D018448:Models, Immunological; D012641:Selection, Genetic