Artificial Immune System based on Hybrid and External Memory for Mathematical Function Optimization

Yap, David F. W. and Koh, S. P. and Tiong, S. K. (2011) Artificial Immune System based on Hybrid and External Memory for Mathematical Function Optimization. In: 2011 IEEE Symposium on Computers & Informatics, 20-22 March 2011, Kuala Lumpur.

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Artificial immune system (AIS) is one of the natureinspired algorithm for optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be further improved because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. Thus, a hybrid PSO-AIS and a new external memory CSA based scheme called EMCSA are proposed. In hybrid PSO-AIS, the good features of PSO and AIS are combined in order to reduce any limitation. Alternatively, EMCSA captures all the best antibodies into the memory in order to enhance global searching capability. In this preliminary study, the results show that the performance of hybrid PSO-AIS compares favourably with other algorithms while EMCSA produced moderate results in most of the simulations.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: clonal selection, antibody, antigen,affinity maturation, mutation.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Electronics and Computer Engineering > Department of Telecommunication Engineering
Depositing User: Dr David Yap
Date Deposited: 10 Jul 2012 02:07
Last Modified: 28 May 2015 02:39
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