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ISCI
2007
130views more  ISCI 2007»
13 years 10 months ago
Computing with words and its relationships with fuzzistics
ct 9 Words mean different things to different people, and so are uncertain. We, therefore, need a fuzzy set model for a word 10 that has the potential to capture their uncertaint...
Jerry M. Mendel
TFS
2008
190views more  TFS 2008»
13 years 10 months ago
A Fast Geometric Method for Defuzzification of Type-2 Fuzzy Sets
Generalised type-2 fuzzy logic systems can not currently be used for practical problems because the amount of computation required to defuzzify a generalised type-2 fuzzy set is to...
Simon Coupland, Robert John
IWANN
2009
Springer
14 years 5 months ago
Fuzzy Logic, Soft Computing, and Applications
We survey on the theoretical and practical developments of the theory of fuzzy logic and soft computing. Specifically, we briefly review the history and main milestones of fuzzy ...
Inma P. Cabrera, Pablo Cordero, Manuel Ojeda-Acieg...
EUSFLAT
2009
114views Fuzzy Logic» more  EUSFLAT 2009»
13 years 8 months ago
The Use of Interval-Valued Probability Measures in Fuzzy Linear Programming: a constraint set approach
This paper uses a constraint set approach to linear programming problems with equality constraints whose coefficients and/or right-hand side values could be uncertain. We consider ...
Phantipa Thipwiwatpotjana, Weldon A. Lodwick
FUZZIEEE
2007
IEEE
14 years 5 months ago
On the Accuracy of Type-2 Fuzzy Sets
— Geometric Type-2 Fuzzy sets allow us to model type-2 fuzzy sets using geometry providing significant improvement in speed of computation. This paper explores in detail how wel...
Simon Coupland, Robert John