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Cardinality, Fuzziness, Variance and Skewness of Interval Type-2 Fuzzy Sets
2007 IEEE Symposium on Foundations of Computational Intelligence, 2007Centroid, cardinality, fuzziness, variance and skewness are all important concepts for an interval type-2 fuzzy set (IT2 FS) because they are all measures of uncertainty, i.e. each of them is an interval, and the length of the interval is an indicator of the uncertainty. The centroid of an IT2 FS has been defined by Karnik and Mendel.
Jerry M. Mendel, Dongrui Wu
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Modeling words by normal interval type-2 fuzzy sets
2014 IEEE Conference on Norbert Wiener in the 21st Century (21CW), 2014In this paper, we propose a new method-the HM method-to model words by normal IT2 FSs, using data intervals that are collected from a group of subjects. The HM method uses the same bad data processing, outlier processing and tolerance limit processing to pre-process the data intervals, as is used in the Enhanced Interval Approach (EIA); it then uses a ...
Minshen Hao, Jerry M. Mendel
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A similarity measure between interval type-2 fuzzy sets
2010 IEEE International Conference on Mechatronics and Automation, 2010The fuzzy similarity measure shows the similar degree of two fuzzy sets (FSs) and can be used in various areas. There are numerous studies as to it on type-1 fuzzy sets (T1 FSs), but little attention has been received on type-2 fuzzy sets (T2 FSs). In this paper, a new similarity measure between interval type-2 fuzzy sets (IT2 FSs) is proposed. Firstly,
Gao Zheng +3 more
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Perceptual reasoning using interval type-2 fuzzy sets: Properties
2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), 2008Perceptual reasoning (PR) is an approximate reasoning mechanism that can be used as a computing with words (CWW) Engine, i.e., given input words, PR can infer the output from a rulebase. When the input words and the words in the rulebase are modeled by interval type-2 fuzzy sets (IT2 FSs), the output of PR, YtildePR, is also an IT2 FS, and it will be ...
null Dongrui Wu, Jerry M. Mendel
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Interval-Valued and Interval Type-2 Fuzzy Sets: A Subjective Comparison
2007 IEEE International Fuzzy Systems Conference, 2007The paper contains remarks on similarities and differences between interval-valued and interval type-2 fuzzy sets. The definitions of basic characteristics, like cardinality or support, are provided and related to the sets. The canonical forms of linguistically quantified propositions under both groups of interval sets, are discussed and real and ...
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The Reduction of Interval Type-2 LR Fuzzy Sets
IEEE Transactions on Fuzzy Systems, 2014Type reduction of interval type-2 (IT2) fuzzy sets is essential in conducting the type-2 fuzzy sets expressed with the resolution forms of IT2 fuzzy sets. Several type reduction methods, such as KM, EKM, and centroid flow, have been proposed. These methods are relatively easy to implement but still computation-intensive because they need to invoke an ...
Chao-Lieh Chen +2 more
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Construction of Interval Type-2 Fuzzy Sets From Fuzzy Sets: Methods and Applications
2013In this chapter, we present some methods to construct interval type-2 membership functions from fuzzy membership functions and their applications in image processing, classification, and decision making. First, we review some basic concepts of interval type-2 fuzzy sets (IT2FSs).
Miguel Pagola +9 more
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On Defuzzification of Interval Type-2 Fuzzy Sets
2008In the paper the defuzzification of interval type-2 fuzzy sets is studied. The standard K-M type-reduction method and the uncertainty bounds approximate type-reduction are compared with the classical defuzzification of averaged type-1 fuzzy sets.
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Supplier Selection Using Ranking Interval Type-2 Fuzzy Sets
2015In face of global competition, supplier management is emerging as crucial issue to any companies striving for business success. This paper develops a framework for selecting suitable outsourced suppliers of upstream supply chain in uncertain environment.
Samarjit Kar, Kajal Chatterjee
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Generalising Social Structure Using Interval Type-2 Fuzzy Sets
2016To understand the operation of the informal social sphere in human or artificial societies, we need to be able to identify their existing behavioural conventions (institutions). This includes the contextualisation of seemingly objective facts with subjective assessments, especially when attempting to capture their meaning in the context of the analysed
Christopher K. Frantz +3 more
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