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  • The theoretical background for abstract formalization of vague phenomenon of the complex systems is fuzzy set theory. In the paper vague data as specialized fuzzy sets - fuzzy numbers are defined and it is described a fuzzy linear regression model as a fuzzy function with fuzzy numbers as vague parameters. Interval and fuzzy regression technologies are discussed, the linear fuzzy regression model is proposed. To identify fuzzy regression coeffcients of model genetic algorithm is applied. The numerical example is presented and the possibility area of vague model is illustrated.
  • The theoretical background for abstract formalization of vague phenomenon of the complex systems is fuzzy set theory. In the paper vague data as specialized fuzzy sets - fuzzy numbers are defined and it is described a fuzzy linear regression model as a fuzzy function with fuzzy numbers as vague parameters. Interval and fuzzy regression technologies are discussed, the linear fuzzy regression model is proposed. To identify fuzzy regression coeffcients of model genetic algorithm is applied. The numerical example is presented and the possibility area of vague model is illustrated. (en)
Title
  • Fuzzy linear regression analysis
  • Fuzzy linear regression analysis (en)
skos:prefLabel
  • Fuzzy linear regression analysis
  • Fuzzy linear regression analysis (en)
skos:notation
  • RIV/61989100:27240/13:86089026!RIV14-MSM-27240___
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  • S
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  • 76081
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  • RIV/61989100:27240/13:86089026
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  • Vagueness; Regression model; Possibility area; Non-specificity; Interval model; Genetic algorithms; Fuzzy number; Fuzzy model (en)
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  • [C404364ADEA3]
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  • Velké Karlovice
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  • London
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  • IFAC Proceedings Volumes (IFAC-PapersOnline). Volume 12, Issue PART 1
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  • Pokorný, Miroslav
  • Nowaková, Jana
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issn
  • 1474-6670
number of pages
http://bibframe.org/vocab/doi
  • 10.3182/20130925-3-CZ-3023.00079
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  • IFAC
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  • 978-3-902823-53-3
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  • 27240
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