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Journal Article

Fuzzy metrics and statistical metric spaces

01 Jan 1975-Kybernetika (Institute of Information Theory and Automation AS CR)-Vol. 11, Iss: 5, pp 336-344
TL;DR: The aim of this paper is to apply the concept of fuzziness to the clasical notions of metric and metric spaces and to compare the obtained notions with those resulting from some other, namely probabilistic statistical, generalizations of metric spaces.
Abstract: The adjective "fuzzy" seems to be a very popular and very frequent one in the contemporary studies concerning the logical and set-theoretical foundations of mathematics. The main reason of this quick development is, in our opinion, easy to be understood. The surrounding us world is full of uncertainty, the information we obtain from the environment, the notions we use and the data resulting from our observation or measurement are, in general, vague and incorrect. So every formal description of the real world or some of its aspects is, in every case, only an approxima­ tion and an idealization of the actual state. The notions like fuzzy sets, fuzzy orderings, fuzzy languages etc. enable to handle and to study the degree of uncertainty mentioned above in a purely mathematic and formal way. A very brief survey of the most interest­ ing results and applications concerning the notion of fuzzy set and the related ones can be found in [l]. The aim of this paper is to apply the concept of fuzziness to the clasical notions of metric and metric spaces and to compare the obtained notions with those resulting from some other, namely probabilistic statistical, generalizations of metric spaces. Our aim is to write this paper on a quite self-explanatory level the references being necessary only for the reader wanting to study these matters in more details.
Citations
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Journal ArticleDOI
TL;DR: In this paper, a Hausdorff topology on a fuzzy metric space was defined, and Baire's theorem for fuzzy metric spaces was proved for the first time in the fuzzy metric domain.

1,325 citations

Journal ArticleDOI
TL;DR: In this paper, the well-known fixed point theorems of Banach and Edelstein are extended to fuzzy metric spaces in the settle of Kramosil and Michalek.

824 citations

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TL;DR: The distance between two points in a fuzzy metric space is a non-negative, upper semicontinuous, normal and convex fuzzy number.

738 citations

Journal ArticleDOI
TL;DR: Sgurev et al. as discussed by the authors defined the notion of intuitionistic fuzzy metric spaces and proved Baire's theorem and the Uniform limit theorem for intuitionistic metric spaces using fuzzy sets.
Abstract: Using the idea of intuitionistic fuzzy set due to Atanassov [Intuitionistic fuzzy sets. in: V. Sgurev (Ed.), VII ITKR's Session, Sofia June, 1983; Fuzzy Sets Syst. 20 (1986) 87], we define the notion of intuitionistic fuzzy metric spaces as a natural generalization of fuzzy metric spaces due to George and Veeramani [Fuzzy Sets Syst. 64 (1994) 395] and prove some known results of metric spaces including Baire's theorem and the Uniform limit theorem for intuitionistic fuzzy metric spaces.

465 citations

Journal ArticleDOI
TL;DR: It is proved that a subspace of a separable fuzzy metric space is separable and every separable warm fuzzy metricspace is second countable.

411 citations

References
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Journal ArticleDOI

1,997 citations


"Fuzzy metrics and statistical metri..." refers methods in this paper

  • ...In [5] the author follows the pattern used in the process of abstract definition of topological spaces and investigates in which measure this pattern can be followed supposing that instead of "usual" sets the fuzzy sets are considered....

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Book ChapterDOI
01 Jan 1974
TL;DR: This paper attempts to demonstrate the usefulness of fuzziness for a methodology in the behavioral sciences by showing generalizations of non-fuzzy concepts.
Abstract: This paper attempts to demonstrate the usefulness of fuzziness for a methodology in the behavioral sciences. For this purpose, fundamental and interrelated concepts as those of a set, an ordering, a language and a system arc discussed. Several examples and prospective applications are given, in particular by showing generalizations of non-fuzzy concepts. There is a particular emphasis on applications in economics.

12 citations

Journal ArticleDOI

5 citations


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