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Fuzzy information and database systems

โœ Scribed by Janusz Kacprzyk; Bill P. Buckles; Frederick E. Petry


Publisher
Elsevier Science
Year
1990
Tongue
English
Weight
156 KB
Volume
38
Category
Article
ISSN
0165-0114

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๐Ÿ“œ SIMILAR VOLUMES


Fuzzy information in extended fuzzy rela
โœ Ding-An Chiang; Louis R. Chow; Nan-Chen Hsien ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 957 KB

The queries on type-2 fuzzy relational databases may get non-reasonable answers, and as pointed out by Buckles, a tuple's membership value is not static but is a measure of the appropriateness of that tuple to a given query. Here, we use two supplementary attributes/,t, and le to model the concepts

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โœ Z. M. Ma; F. Mili ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 111 KB

Two kinds of fuzziness in attribute values of the fuzzy relational databases can be distinguished: One is that attribute values are possibility distributions, and the other is that there are resemblance relations in attribute domains. The fuzzy relational databases containing these two kinds of fuzz

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โœ Jae Dong Yang ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 161 KB

There are two aspects of uncertainty: vagueness and ambiguity. This paper proposes IP (Implicit Predicate) to support both vagueness and ambiguity in fuzzy databases by allowing disjunctive fuzzy information. IP is basically a descriptor dedicated to an unknown value which turns out to be ambiguous

Handling indefinite and maybe informatio
โœ Nan-Chen Hsieh ๐Ÿ“‚ Article ๐Ÿ“… 2004 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 174 KB

In this article, fuzzy set theory uses an extension of the classical logical relational database model. A logical fuzzy relational database model was developed with the aim of manipulating imprecise information and adding deduction capabilities to the database system. The essence of this work is the