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Interval-Valued Intuitionistic Fuzzy Sets

E-bookPDFE-book
Ranking125363in
CHF118.00

Description

The book offers a comprehensive survey of interval-valued intuitionistic fuzzy sets. It reports on cutting-edge research carried out by the founder of the intuitionistic fuzzy sets, Prof. Krassimir Atanassov, giving a special emphasis to the practical applications of this extension. A few interesting case studies, such as in the area of data mining, decision making and pattern recognition, among others, are discussed in detail.



The book offers the first comprehensive guide on interval-valued intuitionistic fuzzy sets. By providing the readers with a thorough survey and important practical details, it is expected to support them in carrying out applied research and to encourage them to test the theory behind the sets for new advanced applications. The book is a valuable reference resource for graduate students and researchers alike.
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Details

Additional ISBN/GTIN9783030320904
Product TypeE-book
BindingE-book
FormatPDF
Format notewatermark
Publishing date21/09/2019
Edition1st ed. 2020
Series no.388
Pages200 pages
LanguageEnglish
IllustrationsXI, 200 p. 69 illus., 1 illus. in color.
Article no.16803146
CatalogsVC
Data source no.2269744
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Series

Author

Krassimir Atanassov is a Professor and the Head of the Department of "Bioinformatics and Mathematical Modelling" at the Bulgarian Academy of Sciences. In 2013 he received the Award "Pythagoras" from the Ministry of Education, Youth and Science of Bulgaria, as an established researcher in the area of Technical sciences. Since the same year, he has also been fellow of the International Fuzzy Systems Association. His research interests cover the areas of Petri Nets, Fuzzy Sets and Number Theory. In the field of fuzzy sets, he developed the theory of intuitionistic fuzzy sets and showed their applications to artificial intelligence, systems theory, medicine, etc.



He has been serving as E-i-C of different journals. He is the author of numerous monographs, including the book Intuitionistic Fuzzy Logics (Springer, 2017).

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