New geometric inference techniques for type-2 fuzzy sets
International Journal of Approximate Reasoning
Efficient triangular type-2 fuzzy logic systems
International Journal of Approximate Reasoning
Replica technique for geometric modelling
WSEAS Transactions on Information Science and Applications
On constructing parsimonious type-2 fuzzy logic systems via influential rule selection
IEEE Transactions on Fuzzy Systems
An interval fuzzy controller for vehicle active suspension systems
IEEE Transactions on Intelligent Transportation Systems
A simplified architecture for triangular quasi type-2 fuzzy logic systems
International Journal of Computational Intelligence Studies
A 2uFunction representation for non-uniform type-2 fuzzy sets: Theory and design
International Journal of Approximate Reasoning
Fixed charge transportation problem with type-2 fuzzy variables
Information Sciences: an International Journal
General type-2 fuzzy logic systems based on refinement constraint triangulated irregular network
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Generalized type-2 fuzzy logic systems cannot currently be used for practical problems because the amount of computation required to defuzzify a generalized type-2 fuzzy set is too large. This paper presents a new method for defuzzifing a type-2 fuzzy set. The new much faster technique is based on geometric representations and operations. The results of a real world example contained in this paper show this new approach to be over 200,000 times faster than type-reduction. We present a new method for assessing the accuracy of the membership function of a type-2 fuzzy set. This method is used to show that the new representation used by the defuzzifier is not detrimental to the accuracy of the set. We also discuss the differences between the new approach and type-reduction, identifying the origin of this massive improvement in execution speed.