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Some general comments on fuzzy sets of type-2
International Journal of Intelligent Systems, 2009Summary: This paper contains some general comments on the algebra of truth values of fuzzy sets of type 2. It details the precise mathematical relationship with the algebras of truth values of ordinary fuzzy sets and of interval-valued fuzzy sets. Subalgebras of the algebra of truth values and t-norms on them are discussed.
Walker, Carol L., Walker, Elbert A.
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2015
In this paper, we introduce specific types of intuitionistic fuzzy sets, inspired by the multi-dimensional intuitionistic fuzzy sets and the General Type-2 fuzzy sets. The newly proposed sets extend the opportunities of the General Type-2 fuzzy sets when modelling of particular types of uncertainty.
Oscar Castillo +3 more
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In this paper, we introduce specific types of intuitionistic fuzzy sets, inspired by the multi-dimensional intuitionistic fuzzy sets and the General Type-2 fuzzy sets. The newly proposed sets extend the opportunities of the General Type-2 fuzzy sets when modelling of particular types of uncertainty.
Oscar Castillo +3 more
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An inclusion measure between general type-2 fuzzy sets
2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010The inclusion measure indicates the degree that a fuzzy set is contained in another fuzzy set and can be used in many fields. However, the inclusion measure between type-2 fuzzy sets has received little attention. Hence in this paper, we propose an inclusion measure for general type-2 fuzzy sets.
Gao Zheng +3 more
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Soft Computing, 2019
The Karnik–Mendel (KM) or the enhanced Karnik–Mendel (EKM) algorithm is widely used for interval type-2 fuzzy sets type reduction in many applications. Compared with iterative procedures of KM/EKM, an iterative algorithm with a stop condition or an enhanced iterative algorithm with a stop condition based on the KM algorithm that converges monotonically
Shi Jianzhong +3 more
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The Karnik–Mendel (KM) or the enhanced Karnik–Mendel (EKM) algorithm is widely used for interval type-2 fuzzy sets type reduction in many applications. Compared with iterative procedures of KM/EKM, an iterative algorithm with a stop condition or an enhanced iterative algorithm with a stop condition based on the KM algorithm that converges monotonically
Shi Jianzhong +3 more
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Enhanced centroid-flow algorithm for general type-2 fuzzy sets
2011 Annual Meeting of the North American Fuzzy Information Processing Society, 2011The Centroid Flow (CF) algorithm is a newly proposed approach for computing the centroid of a type-2 fuzzy set A, which normally can be obtained by taking the union of the centroids of all the α-planes of A. The CF algorithm utilizes the Karnik-Mendel (KM) or the Enhanced KM (EKM) algorithm only once at the α = 0 α-plane, and then lets its result ...
Daoyuan Zhai, Jerry M. Mendel
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Importance sampling based defuzzification for general type-2 fuzzy sets
International Conference on Fuzzy Systems, 2010General type-2 fuzzy logic systems (T2 FLS) constitute a powerful tool for coping with ubiquitous uncertainty in many engineering applications. However, the immense computational complexity associated with defuzzification of general T2 fuzzy sets still remains an unresolved issue and prohibits its practical use.
Ondrej Linda, Milos Manic
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zSlices Based General Type-2 Fuzzy Sets and Systems
2013This chapter provides a concise introduction to zSlices based general type-2 fuzzy sets and their associated set-theoretic operations. zSlices based general type-2 fuzzy sets allow the representation of and computation with general type-2 fuzzy sets by modeling each fuzzy set as a series of zSlices, i.e., modified interval type-2 fuzzy sets, thus ...
Wagner, C, Hagras, H
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General type-2 fuzzy rough sets based on $$\alpha $$ α -plane Representation theory
Soft Computing, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhao, Tao, Xiao, Jian
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Matching general type-2 fuzzy sets by comparing the vertical slices
2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013In this paper, we propose a procedure for computing the dissimilarity measure of finite general type-2 fuzzy sets, represented as sequences of vertical slices. Through representing general type-2 fuzzy sets as a sequence of objects, we compute their overall dissimilarity value using suited matching algorithms for generalized sequences.
RIZZI, Antonello +3 more
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General type-2 FLS with uncertainty generated by fuzzy rough sets
International Conference on Fuzzy Systems, 2010In this paper, in the framework of the type-2 fuzzy logic system (FLS), a concept of fuzzification by fuzzy rough sets is introduced. The notion of the general type-2 fuzzy set is found to be concurrent with the fuzzy rough set in the sense of Nakamura.
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