Type-2 fuzzy sets and systems

Type-2 fuzzy sets and systems generalize Type-1 fuzzy sets and systems so that more uncertainty can be handled. From the very beginning of fuzzy sets… (More)
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Topic mentions per year

Topic mentions per year

1972-2017
05101519722017

Papers overview

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2015
2015
This article provides a high-level retrospective of type-2 fuzzy sets and fuzzy logic systems. It explains how type-2 fuzzy sets… (More)
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2015
2015
Many different real-world applications with a high-level of uncertainty proved the good performance of the type-2 fuzzy sets (T2… (More)
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2012
2012
General Type-2 Fuzzy Sets (GT2 FSs) have been originally proposed to allow for modeling uncertainty associated with the… (More)
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Highly Cited
2011
Highly Cited
2011
Type-reduction algorithms are very important for type-2 fuzzy sets and systems. The earliest one, and also the most popular one… (More)
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2010
2010
As part of this paper we are highlighting several - in our opinion- important aspects of type-2 fuzzy logic systems which seem… (More)
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Highly Cited
2007
Highly Cited
2007
In this state-of-the-art paper, important advances that have been made during the past five years for both general and interval… (More)
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Review
2007
Review
2007
As originally published in the February 2007 issue of IEEE Computational Intelligence Magazine, the above titled paper (ibid… (More)
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2007
2007
The Karnik-Mendel (KM) algorithms are iterative procedures widely used in fuzzy logic theory. They are known to converge… (More)
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2007
2007
Interval type-2 fuzzy sets (IT2 FS) play a central role in fuzzy sets as models for words and in engineering applications of T2… (More)
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Highly Cited
2006
Highly Cited
2006
Interval type-2 fuzzy sets (T2 FS) play a central role in fuzzy sets as models for words and in engineering applications of T2… (More)
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