A support vector-based interval type-2 fuzzy system

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A support vector-based interval type-2 fuzzy system

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 ar...

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Bibliographic Details
Main Authors:	Uslan, V., Seker, H., John, Robert
Format:	Conference or Workshop Item
Published:	2014
Subjects:	fuzzy set theory;regression analysis;support vector machines;IF-THEN rules;efficient closed-form type reduction strategy;fuzzy regression model;generalisation performance;nonlinear system approximation;support vector machines;support vector regression;support vector-based interval type-2 fuzzy system;Approximation methods;Computational modeling;Fuzzy sets;Fuzzy systems;Predictive models;Support vector machines;Time series analysis
Online Access:	https://eprints.nottingham.ac.uk/27775/

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