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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Interval Type-2 Fuzzy Markov Chains: Type Reduction
verfasst von : Juan C. Figueroa-García, Dusko Kalenatic, Cesar Amilcar Lopez
Erschienen in: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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This paper shows an application of Type-reduction algorithms for computing the steady state of an Interval Type-2 Fuzzy Markov Chain (IT2FM). The IT2FM approach is an extension of the scope of a Type-1 fuzzy markov chain (T1FM) that allows to embed several Type-1 fuzzy sets (T1FS) inside its
Footprint of Uncertainty
. In this way, a finite state Fuzzy Markov Chain process is defined on an Interval Type-2 Fuzzy environment, finding their limiting properties and its Type-reduced behavior. To do so, two examples are provided.