Bifurcating fuzzy sets: Theory and application
Neurocomputing
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To reduce the computational burden of the type reduction block of interval type-2 fuzzy logic systems (IT2FLSs), this paper presents an efficient interval-analysis based type-reduction method to replace the most widely used center-of-sets (COS) type-reduction method which utilizes the iterative Karnik-Mendel algorithm. The relationships between the proposed type-reduction method and the COS type-reduction method are also discussed. Simulation results show that the proposed type-reduction method can present satisfactory performance. Moreover, from the view of computational complexity, the proposed type-reduction method is much more efficient than the COS type-reduction method.