Rough Set (Rough Set) Reduction System Software

Most existing database systems, such as SQL Server, have the advantages of high access efficiency, high storage space utilization, and suitable for large-scale data storage, therefore, we use the SQL language to implement the set operation of rough sets, and use a high-performance database management system to implement data mining of rough sets. This not only enables knowledge acquisition of large-scale data, but also enables efficient data processing.

The system uses VC #. to achieve better efficiency, the system uses SQL Server Stored Procedures to perform database operations, and then uses VC #.. Net program calls the stored procedure. The system has a Pentium 4 1.80ghz processor and MB of memory, 20g Hard Disk Space: Run in Microsoft Windows XP Service Pack 2, Microsoft. NET Framework SDK V1.1, and Microsoft SQL Server 2000.

This system is mainly used to process information systems and decision tables. It can obtain data sets from different data sources and input them to the system for the operation of the system. You can select an Attribute Set (or condition attribute and decision attribute) to generate an Information System (decision table) and save it to the current operation table for preprocessing, by selecting an appropriate Attribute Reduction Method (positive region, difference matrix, and information entropy), we can perform Attribute Reduction and analyze the correctness and independence of the reduction results. If the current operation is a decision table, you can reduce the values to generate a rule set, and enter a new object set to verify the correctness of the rule.

 

Flowchart of Knowledge Acquisition System Based on relational database and Rough Set Theory

Knowledge Acquisition System Interface Based on relational database and Rough Set Theory

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