Fuzzy Inference Rule Generation Using Genetic AlgorithmVariant
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 4
Abstract
Abstract: In essence of fuzzy inference system (FIS) for classification, Genetic algorithm (GA) which is anoptimal searching technique is used for generation rules in the proposed work. This paper develops an FIS withrules generated using GA, the GA is developed with rule importance as fitness criteria. The rule importance ofeach rule is calculated by its rule support in each rule class. Encoding of rules is using the fuzzy membership setno for antecedent and consequent. Also the stopping criteria is a combination ofgenerations specified andMinimum rules fired count. The Proposed system using GA approach for rule generation giving consistentresults with optimal rules.
Authors and Affiliations
Shruti S. Jamsandekar , Ravindra R. Mudholkar
Keywords
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