Automatic bandwidth selection of fuzzy membership functions
Information Sciences: an International Journal
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Generating fuzzy membership function with self-organizing feature map
Pattern Recognition Letters
Dynamical membership functions: an approach for adaptive fuzzy modelling
Fuzzy Sets and Systems
H∞ estimation for fuzzy membership function optimization
International Journal of Approximate Reasoning
Handling constraints in global optimization using an artificial immune system
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
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A clonal selection algorithm (CLONALG) inspires from Clonal Selection Principle used to explain the basic features of an adaptive immune response to an antigenic stimulus. In this study, a new method is proposed for optimization of the Multiple Input Single Output (MISO) fuzzy membership functions using CLONALG. The most appropriate placement of membership functions with respect to fuzzy variables can be determined using our method for a fuzzy system whose rules table and shape of membership functions were given previously. Also, how the membership functions compute as a parameter optimization problem using CLONALG is descried for MISO fuzzy system on an illustrative example.