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A Dynamic Dominance-Based Rough Set Approach for Processing Ordered Data

机译:基于动态的基于优势的粗糙集方法,用于处理有序数据

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In real-world many information systems are varying over time. How to process efficiently dynamic data is a hot issue in data mining research field. Processing information with preference-ordered attribute domain is an important task in multi-criteria decision mak-ing. Since dominance-based rough set approach can process information with preference-ordered attribute domain, it has been applied widely to rnulti-criteria decision making. In the paper, we introduce a new strat-egy of updating approximations in DRSA under the cases when a lot of objects being added. For thus, the notation of base boundaries of approximations in DRSA is given to reduce the redundant computation in updating approximations. The feasibility of the approach was vali-dated by a numerical example.
机译:在现实世界中,许多信息系统随着时间的推移而变化。如何处理有效的动态数据是数据挖掘研究领域的一个热门问题。处理信息与优先订购的属性域是多标准决策中的重要任务。由于基于优势的粗略集合方法可以使用优先订购的属性域来处理信息,因此它已被广泛应用于Rnulti-Criteria决策。在论文中,我们在添加大量对象时介绍了在DRSA中更新近似值的新Strat-egy。因此,给出了DRSA中近似的基地边界的符号,以减少更新近似的冗余计算。该方法的可行性是由数值示例进行的。

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