Properties of the nearest parametric form approximation operator of fuzzy numbers.
Amirfakhrian, Majid (2010)
Analele Ştiinţifice ale Universităţii “Ovidius" Constanţa. Seria: Matematică
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Amirfakhrian, Majid (2010)
Analele Ştiinţifice ale Universităţii “Ovidius" Constanţa. Seria: Matematică
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Vilém Novák (2001)
Acta Mathematica et Informatica Universitatis Ostraviensis
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I. M. Hanafy (2003)
Czechoslovak Mathematical Journal
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In this paper, after giving the basic results related to the product of functions and the graph of functions in intuitionistic fuzzy topological spaces, we introduce and study the concept of fuzzy completely continuous functions between intuitionistic fuzzy topological spaces.
Çoker, Doğan, Eş, A.Haydar, Turanli, Necla (2004)
International Journal of Mathematics and Mathematical Sciences
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Adam Grabowski (2017)
Formalized Mathematics
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In the article we present in the Mizar system the catalogue of nine basic fuzzy implications, used especially in the theory of fuzzy sets. This work is a continuation of the development of fuzzy sets in Mizar; it could be used to give a variety of more general operations, and also it could be a good starting point towards the formalization of fuzzy logic (together with t-norms and t-conorms, formalized previously).
Martine De Cock, Etienne Kerre (2002)
International Journal of Applied Mathematics and Computer Science
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We present a framework of L-fuzzy modifiers for L being a complete lattice. They are used to model linguistic hedges that act on linguistic terms represented by L-fuzzy sets. In the modelling process the context is taken into account by means of L-fuzzy relations, endowing the L-fuzzy modifiers with a clear inherent semantics. To our knowledge, these L-fuzzy modifiers are the first ones proposed that are suitable to perform this representation task for a lattice L different from the...
Ramadan, A.A., Abbas, S.E., Abd El-Latif, A.A. (2005)
International Journal of Mathematics and Mathematical Sciences
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Robert K. Nowicki (2010)
International Journal of Applied Mathematics and Computer Science
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The paper presents a new approach to fuzzy classification in the case of missing data. Rough-fuzzy sets are incorporated into logical type neuro-fuzzy structures and a rough-neuro-fuzzy classifier is derived. Theorems which allow determining the structure of the rough-neuro-fuzzy classifier are given. Several experiments illustrating the performance of the roughneuro-fuzzy classifier working in the case of missing features are described.
Wu, Kweimei (2003)
International Journal of Mathematics and Mathematical Sciences
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