Results 151 to 160 of about 119,525 (201)

Uncertainty measures for interval type-2 fuzzy sets

Information Sciences, 2007
Based on the representation theorem for interval type-2 fuzzy sets, 4 types of new uncertainty measures are introduced and discussed, namely cardinality, fuzziness, variance and skewness. Note that the first uncertainty measures for this type of fuzzy sets, namely the centroid, was introduced already in [\textit{N. N. Karnik} and \textit{J. M. Mendel},
Wu, Dongrui, Mendel, Jerry M.
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Fuzzy analytic hierarchy process with interval type-2 fuzzy sets

Knowledge-Based Systems, 2014
The membership functions of type-1 fuzzy sets have no uncertainty associated with it. While excessive arithmetic operations are needed with type-2 fuzzy sets with respect to type-1's, type-2 fuzzy sets generalize type-1 fuzzy sets and systems so that more uncertainty for defining membership functions can be handled.
Cengiz Kahraman, Başar Öztayşi, İrem Uçal Sarı, Ebru Turanoğlu   +3 more
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On Computing Normalized Interval Type-2 Fuzzy Sets

IEEE Transactions on Fuzzy Systems, 2014
This paper explains how to compute normalized interval type-2 fuzzy sets in closed form and explains how the results reduce to well-known results for type-1 fuzzy sets and interval sets. Such normalized interval type-2 fuzzy sets may be needed in linguistic probability computa- tions or multiple criteria decision analysis under uncertainty. Index Terms—
Jerry M. Mendel, Mohammad Reza Rajati
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Closed form fuzzy interpolation with interval type-2 fuzzy sets

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2014
Fuzzy rule interpolation enables fuzzy inference with sparse rule bases by interpolating inference results, and may help to reduce system complexity by removing similar (often redundant) neighbouring rules. In particular, the recently proposed closed form fuzzy interpolation offers a unique approach which guarantees convex interpolated results in a ...
Longzhi Yang, Chengyuan Chen, Nanlin Jin, Xin Fu, Qiang Shen   +4 more
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Fuzzy feature selection based on interval type-2 fuzzy sets

SPIE Proceedings, 2017
When dealing with real world data; noise, complexity, dimensionality, uncertainty and irrelevance can lead to low performance and insignificant judgment. Fuzzy logic is a powerful tool for controlling conflicting attributes which can have similar effects and close meanings. In this paper, an interval type-2 fuzzy feature selection is presented as a new
Sahar Cherif, Nesrine Baklouti, Adel Alimi, Vaclav Snasel   +3 more
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On interval type-2 rough fuzzy sets

Knowledge-Based Systems, 2012
In this paper, we present a general framework for the study of interval type-2 rough fuzzy sets by using both constructive and axiomatic approaches. First, several concepts and properties of interval type-2 fuzzy sets are introduced. Then, a pair of lower and upper interval type-2 rough fuzzy approximation operators with respect to a crisp binary ...
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An Entropy of Interval Type-2 Fuzzy Sets

Applied Mechanics and Materials, 2013
The entropy shows the fuzzy degree of a fuzzy set (FS) and can be used in various areas. Aiming at the characteristics of the fuzzy entropy and type-2 fuzzy sets (IT2 FSs), we introduce a new entropy of IT2 FSs in this paper. At first, we select an axiomatic definition for it.
Gao Zheng, Shi Wei Yin
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Embedded interval valued type-2 fuzzy sets

2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291), 2003
Type-2 fuzzy sets are growing in popularity as, for certain applications they model uncertainty and imprecision better than type-1 fuzzy sets. However, type-2 fuzzy sets can be difficult to understand and explain. Recent work has introduced embedded type-2 fuzzy sets and the representation theorem which enable us to discuss type-2 fuzzy sets in a ...
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Three-way decisions based on type-2 fuzzy sets and interval-valued type-2 fuzzy sets

Journal of Intelligent & Fuzzy Systems, 2016
This paper investigates three-way decisions of type-2 fuzzy sets and interval-valued type-2 fuzzy sets based on partially ordered sets. First, the partially ordered sets, constituted by fuzzy truth values and interval-valued fuzzy truth values, are established, respectively. They serve as the basic structures of three-way decision spaces.
Xiao, Yuan Chun, Hu, Bao Qing, Zhao, Xue Rong   +2 more
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Fuzzy Interpolative Reasoning Using Interval Type-2 Fuzzy Sets

2008
In this paper, we present a new fuzzy interpolative reasoning method using interval type-2 fuzzy sets. We calculate the ranking values through the reference points and the heights of the upper and the lower membership functions of interval type-2 fuzzy sets.
Li-Wei Lee, Shyi-Ming Chen
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