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Description
  • We study the tolerance-based approach to possibilistic nonlinear regression models with interval data. We provide a method for determination of interval regression parameters of the model for the crisp input - interval output case and for the interval input - interval output case. We define two classes of nonlinear regression models for which efficient algorithms exist. We illustrate the theory by examples.
  • We study the tolerance-based approach to possibilistic nonlinear regression models with interval data. We provide a method for determination of interval regression parameters of the model for the crisp input - interval output case and for the interval input - interval output case. We define two classes of nonlinear regression models for which efficient algorithms exist. We illustrate the theory by examples. (en)
Title
  • On the tolerance approach to possibilistic nonlinear regression over interval data
  • On the tolerance approach to possibilistic nonlinear regression over interval data (en)
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  • On the tolerance approach to possibilistic nonlinear regression over interval data
  • On the tolerance approach to possibilistic nonlinear regression over interval data (en)
skos:notation
  • RIV/00216208:11320/12:10125859!RIV13-MSM-11320___
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  • I, P(GAP403/12/1947)
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  • 156480
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  • RIV/00216208:11320/12:10125859
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  • Tolerance quotient; Possibilistic regression; Nonlinear regression; Interval regression (en)
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  • [F0CD66718234]
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  • Brno
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  • Brno
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  • Proceedings of the 5th International Conference on Reliable Engineering Computing
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  • Hladík, Milan
  • Černý, Michal
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  • LITERA
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  • 978-80-214-4507-9
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  • 11320
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