An optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty using genetic algorithms

Authors:
Denisse Hidalgo;Patricia Melin;Oscar Castillo
Affiliations:
School of Engineering, UABC University, Tijuana, Mexico;Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico;Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

This paper proposes an optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty (FOU) of the membership functions, considering three different cases to reduce the complexity problem of searching the parameter space of solutions. For the optimization method, we propose the use of a genetic algorithm (GA) to optimize the type-2 fuzzy inference systems, considering different cases for changing the level of uncertainty of the membership functions to reach the optimal solution at the end.