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This paper presents a newly created significance measure based on a variation of Bayes' theorem, one which quantifies the significance of any value contained within an R-fuzzy set. An R-fuzzy set is a relatively new concept and an extension to fuzzy sets. By utilising the lower and upper approximations from rough set theory, an R-fuzzy approach allows for uncertain fuzzy membership values to be encapsulated...
In this paper, a new fuzzy regression model that is supported by support vector regression is presented. Type-2 fuzzy systems are able to tackle applications that have significant uncertainty. However general type-2 fuzzy systems are more complex than type-1 fuzzy systems. Support vector machines are similar to fuzzy systems in that they can also model systems that are non-linear in nature. In the...
In this paper two contrasting approaches to the defuzzification of generalised type-2 fuzzy sets are investigated. The sampling method is a direct approach, whereas the α-planes method extends interval defuzzification to generalised type-2 sets, and therefore has to be used in conjunction with an interval technique such as the Karnik-Mendel Iterative Procedure. Experimental evaluations are made of...
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