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  • In this work we consider a theory described in [2] where the fuzzy interpolation is based on similarity relations. From our observations we can say that the method presented in [2] solves an approximation problem instead of interpolation. We focused on triangular fuzzy sets and tried to understand the principle of fuzzy rule base interpolation. In our approach we propose to rewrite the technique in [2] using metric distances. We present compositions between similarity relations and fuzzy sets and their properties. All steps are demonstrated in their graphical representation.
  • In this work we consider a theory described in [2] where the fuzzy interpolation is based on similarity relations. From our observations we can say that the method presented in [2] solves an approximation problem instead of interpolation. We focused on triangular fuzzy sets and tried to understand the principle of fuzzy rule base interpolation. In our approach we propose to rewrite the technique in [2] using metric distances. We present compositions between similarity relations and fuzzy sets and their properties. All steps are demonstrated in their graphical representation. (en)
Title
  • Fuzzy Rule Base Interpolation and its Graphical Representation
  • Fuzzy Rule Base Interpolation and its Graphical Representation (en)
skos:prefLabel
  • Fuzzy Rule Base Interpolation and its Graphical Representation
  • Fuzzy Rule Base Interpolation and its Graphical Representation (en)
skos:notation
  • RIV/61988987:17610/10:A1300Z9P!RIV13-MSM-17610___
http://linked.open...avai/riv/aktivita
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  • S
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  • 260128
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  • RIV/61988987:17610/10:A1300Z9P
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  • fuzzy interpolation; fuzzy rule (en)
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http://linked.open...ontrolniKodProRIV
  • [F9FB5A507EDE]
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  • Zittau/Görlitz
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  • Zittau/Görlitz
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  • Proceedings East West Fuzzy Colloquium 2010 / 17th Zittau Fuzzy Colloquim
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  • Perfiljeva, Irina
  • Hoďáková, Petra
  • WRUBLOVÁ, Michaela
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http://linked.open.../riv/zahajeniAkce
number of pages
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  • Neuveden
https://schema.org/isbn
  • 978-3-9812655-4-5
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  • 17610
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