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Fuzzy relational database models generalize the classical relational database model by allowing uncertain and imprecise information to be represented and manipulated. In this paper, we introduced fuzzy extensions of the normal forms for similarity based fuzzy relational database model. First of all we have designed an algorithm to find the fuzzy closure of(More)
In order to model the real world with imprecise and uncertain information, various extensions of the classical relational data model have been studied in literature using fuzzy set theory. However, vague set, as a generalized fuzzy set, has more powerful ability to process fuzzy information than fuzzy set. In this paper, we have proposed a vague relational(More)
The traditional relational database model may be extended into a fuzzy database model based on the mathematical framework of fuzzy set theory to process imprecise or uncertain information. While designing such a fuzzy relational database model that does not suffer from data redundancy and anomalies, the present authors have defined several fuzzy normal(More)
— This paper introduces a new definition of fuzzy multivalued dependency, called α-fmvd, on the basis of the α-equality of tuples as defined in [1]. Next the definition is shown to be consistent, i.e., it reduces to that of classical multivalued dependency (mvd) when the choice parameter takes the value one. Finally, a set of sound and complete inference(More)
In the present paper, we have attempted to process indeterminate data through imprecise queries from a database using neutrosophic set which is based on truth, indeterminacy and false membership values. Firstly, we have introduced a similarity measure formula to measure closeness of two neutrosophic data which in turn is used to get the similarity value for(More)
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