| Summary: | 碩士 === 元智大學 === 資訊管理研究所 === 92 === A fuzzy relational data model is an extension of the traditional relational data model that is mainly to process precise data. However, in the real world, there are a lot of uncertain and imprecise data. In order to deal with imprecise data, Zadeh introduced the theory of fuzzy sets based on the mathematical framework in 1965. In the fuzzy relational data model, different kinds of integrity constraints, such as fuzzy functional dependency, fuzzy multivalued dependency, fuzzy join dependency, etc., were added to relational database to filter and constrain its data according to the requirements of database.
This thesis utilizes the proximity relation of extended-possibility-based model to describe fuzzy data. It proposes a new conception of fuzzy functional dependency and fuzzy multivalued dependency based on conformance and from the point of view of two-tuple relations and its subrelations. In addition, sound and complete inference rules for fuzzy functional dependencies and fuzzy multivalued dependencies presented here can serve as the normalized criteria of fuzzy relational database.
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