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Interval Type-2 Fuzzy Markov Chains: Type Reduction

  • Juan C. Figueroa-García
  • Dusko Kalenatic
  • Cesar Amilcar Lopez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6839)

Abstract

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.

Keywords

Stationary Transition Matrix Type Reduction Fuzzy Matrix Fuzzy Matrice Strong Ergodic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Juan C. Figueroa-García
    • 1
  • Dusko Kalenatic
    • 2
  • Cesar Amilcar Lopez
    • 1
  1. 1.Universidad Distrital Francisco José de CaldasBogotáColombia
  2. 2.Universidad de La SabanaChíaColombia

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