Fuzzy information and database systems
โ 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
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
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
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
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
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