Study And Application Of Attribute Reduction Algorithms Based On Rough Sets

Database Technology has already been developed from original data processing to Database Management System, which can inquire and process transaction. With the further development, the efficient data analysis and data understandability tools are more and more needed. Rough sets is just a mathematical tool to deal with imprecise and inconsistent knowledge. This paper shows three aspects as follow:1. An algorithm of attribute reduction based on discernibility matrix ----ARDM is presented.Through analyzing to the algorithm of attribute reduction based on discernibility matrix, the facts that affect time efficiency are found, and the absorptivity in the proposition calculation is used to the process of constructing the discernibility matrix, then the effectless repeated elements are deleted, accordingly the efficiency of attribute reduction is improved.2. An dynamic algorithm of attribute reduction is presented. In fact, data are always changing in database, so a dynamic algorithm of attribute reduction based on rough logic is presented, which can get new minimum decision algorithm based on the original one when new object is added. It can avoid reduction from large original decision table, update and vindicate the original algorithm, and improve the efficiency of attribute reduction.3. According to the algorithm of attribute reduction, auto-classification system about stellar spectrum data is designed and implemented through using Visual FoxPro 6.0, which automatically extract rules from stellar spectrum.