Results 161 to 170 of about 119,525 (201)

Interval Type-2 Fuzzy Set Reconstruction Based on Fuzzy Information-Theoretic Kernels

IEEE Transactions on Fuzzy Systems, 2015
This paper presents a universal methodology for generating an interval type-2 fuzzy set membership function from a collection of type-1 fuzzy sets. The key idea of the proposed methodology is to designate a specific type-1 fuzzy set as the representative of all input type-1 fuzzy sets.
Hooman Tahayori, LIVI, LORENZO, Alireza Sadeghian, RIZZI, Antonello   +3 more
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Modeling capability of type-1 fuzzy set and interval type-2 fuzzy set

2012 IEEE International Conference on Fuzzy Systems, 2012
Fuzzy logic (FL) has been regarded as a useful methodology in modelling. The modeling performance of FL heavily relies on the modeling capability of a fuzzy set (FS). However, the MF of a FS cannot be arbitrarily accurate in practice and thus the centroid as a measure of a FS cannot be accurate to any degree.
null Maowen Nie, null Woei Wan Tan
openaire   +1 more source

An Interval Approach to Fuzzistics for Interval Type-2 Fuzzy Sets

2007 IEEE International Fuzzy Systems Conference, 2007
In this paper, a new and simple approach, called interval approach, to type-2 fuzzistics is presented, one that captures the strong points of both the person-MF and interval end-points approaches. It uses interval end-point data that are collected from a group of subjects, assumes a probability distribution for each person's data and maps the mean and ...
Feilong Liu, Jerry M. Mendel
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Interval type-2 fuzzy c-means clustering using intuitionistic fuzzy sets

2013 Third World Congress on Information and Communication Technologies (WICT 2013), 2013
In this paper, intuitionistic interval type-2 fuzzy c-means clustering (InIT2FCM) method is proposed for the clustering problems. Intuitionistic fuzzy sets (IFS) and intuitionistic type-2 fuzzy sets (InIT2FS) were introduced with the aim to better handle the uncertainty.
Dzung Dinh Nguyen, Long Thanh Ngo, Long The Pham   +2 more
openaire   +1 more source

Weighted fuzzy interpolative reasoning based on interval type-2 fuzzy sets

2008 International Conference on Machine Learning and Cybernetics, 2008
In this paper, we present a weighted fuzzy interpolative reasoning method for sparse fuzzy rule-based system based on interval type-2 fuzzy sets. Based on the ranking values of interval type-2 fuzzy sets, we present a weighted fuzzy interpolative reasoning method for sparse fuzzy rule-based systems.
null Li-Wei Lee, null Shyi-Ming Chen
openaire   +1 more source

Fuzzy decision making systems based on interval type-2 fuzzy sets

Information Sciences, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chen, Shyi-ming, Wang, Cheng-yi
openaire   +2 more sources

Cardinality, Fuzziness, Variance and Skewness of Interval Type-2 Fuzzy Sets

2007 IEEE Symposium on Foundations of Computational Intelligence, 2007
Centroid, 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
openaire   +1 more source

Modeling words by normal interval type-2 fuzzy sets

2014 IEEE Conference on Norbert Wiener in the 21st Century (21CW), 2014
In 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, 2010
The 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, Jing Wang, Wengwei Zhou, Yong Zhang   +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), 2008
Perceptual 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
openaire   +1 more source