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http://ifigenia.org/wiki/issue:nifs/20/2/85-93
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| Title of paper:
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Data-based approximation of intuitionistic fuzzy target sets
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| Author(s):
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| Ray-Ming Chen
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| Department of Computer Science, Friedrich-Alexander-Universitat Erlangen-Nürnberg, Martenstraße 3, 91058 Erlangen, Germany
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| ray.chen@fau.de
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| Published in:
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"Notes on Intuitionistic Fuzzy Sets", Volume 20, 2014, Number 2, pages 85-93
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| Download:
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 PDF (237 Kb, File info)
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| Abstract:
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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.
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| Keywords:
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Intuitionistic fuzzy target set, Approximation, Messy information system, Data restoration.
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| AMS Classification:
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03E72
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| References:
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- Atanassov, K. T., Intuitionistic fuzzy sets, Fuzzy Sets and Systems, Vol. 20, 1986, 87–96.
- Zadeh, L. A., Fuzzy sets, Information and Control, Vol. 8, 1965, 338–353.
- Pawlak, Z., Rough sets, International Journal of Computer and Information Sciences, Vol. 11, 1982, No. 5, 341–356.
- Pawlak, Z., Rough Sets: Theoretical Aspects of Reasoning about Data, Springer Science+Business Media, Dordrecht, 1991.
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