16-17 May 2019 • Sofia, Bulgaria

Submission: 21 February 2019Notification: 11 March 2019Final Version: 1 April 2019

Issue:Data-based approximation of intuitionistic fuzzy target sets

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Title of paper: Data-based approximation of intuitionistic fuzzy target sets
Author(s):
Ray-Ming Chen
Department of Computer Science, Friedrich-Alexander-Universitat Erlangen-Nürnberg, Martenstraße 3, 91058 Erlangen, Germany
ray.chenAt sign.pngfau.de
Published in: "Notes on IFS", Volume 20, 2014, Number 2, pages 85-93
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Abstract: Approximation is an important process for one to know or recognize a crisp target set. Data reasoning based on an information system is a common source for such approximation. I will introduce how to characterize an intuitionisitc fuzzy target set via a classifier induced by intuitionistic fuzzy sets based on an information system, in particular, a messy information system. I will also show how to restore the data of a messy information system.
Keywords: Intuitionistic fuzzy target set, Approximation, Messy information system, Data restoration.
AMS Classification: 03E72
References:
  1. Atanassov, K. T., Intuitionistic fuzzy sets, Fuzzy Sets and Systems, Vol. 20, 1986, 87–96.
  2. Zadeh, L. A., Fuzzy sets, Information and Control, Vol. 8, 1965, 338–353.
  3. Pawlak, Z., Rough sets, International Journal of Computer and Information Sciences, Vol. 11, 1982, No. 5, 341–356.
  4. Pawlak, Z., Rough Sets: Theoretical Aspects of Reasoning about Data, Springer Science+Business Media, Dordrecht, 1991.
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