Issue:Data-based approximation of intuitionistic fuzzy target sets

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http://ifigenia.org/wiki/issue:nifs/20/2/85-93

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.chen@fau.de Published in: "Notes on Intuitionistic Fuzzy Sets", Volume 20, 2014, Number 2, pages 85-93 Download:  PDF (237  Kb, File info) 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: 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. Citations: The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.