International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 5, No. 8, 8 Jul. 2013
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Data Driven Fuzzy Modeling for Sugeno and Mamdani Type Fuzzy Model using Memetic Algorithm
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Author(s)
Index Terms
Memetic Algorithms (MAs), Genetic Algorithms (GAs ), Fuzzy Modeling, Fuzzy Systems
Abstract
The process of fuzzy modeling or fuzzy model identification is an arduous task. This paper presents the application of Memetic algorithms (MAs) for the identification of complete fuzzy model that includes membership function design for input and output variables and rulebase generation from the numerical data set. We have applied the algorithms on four bench mark data: A rapid Ni-Cd battery charger, the Box & Jenkins’s gas-furnace data, the Iris data classification problem and the wine data classification problem. The comparison of obtained results from MAs with Genetic algorithms (GAs) brings out the remarkable efficiency of MAs. The result suggests that for these problems the proposed approach is better than those suggested in the literature.
Cite This Paper
Savita Wadhawan, Gunjan Goel, Srikant Kaushik, "Data Driven Fuzzy Modeling for Sugeno and Mamdani Type Fuzzy Model using Memetic Algorithm", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.8, pp.24-37, 2013. DOI:10.5815/ijitcs.2013.08.03
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