SQL Processor based on Intelligence Technique:Fuzzy Petri Net Database Applications
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Abstract
Fuzzy concepts with databases have been proposed by numerous scientists for taking care of fuzziness in databases. Fuzzy Petri
net (FPN) expressions are utilized rather than the brittle value of them. However, they discover implementations in areas where
correct or exact value can't generally be acquired. In this paper, to represent the data, we need to specify the field, column, and
table for every fuzzy data are used. Data representation and retrieval in a fuzzy database (F-DB) with the intelligent technique
was invented for the SQL processor of a fuzzy database. The benefits of using the object-oriented databases as the basis in the
fuzzy databases are very significant with SQL schema and using FPN, become an active model tool in the database process. Also,
we investigate the properties of their process by using the FPNs. In our paper outlines the designation of an F-DB language is
called Fuzzy SQL (F-SQL) with FPN, which is used to execute the F-SQL processor. The conventional methods based on SQL
processor is a significant challenge of modeling SQL processor of a fuzzy database which requires a data that is not easy to
accurately gain using either conventional queries, which typically produce noisy or semi-quantitative data. Many studies have
been done in the F-DB in this area, and many valuable approaches have been made. However, the main point is formally
recognized as a critique of an F-DB system's design using the following concept of fuzzy model, must be easy to apply F-DB
applications.
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