Abstract
With the explosive growth and rapid changes in the use of data, information systems are constantly evolving. Timely dynamic updates have become imperative with real-time monitoring of data increasingly common. Effectively characterizing the approximation space in dynamic environments is of significant concern. This paper investigates a dynamic update mechanism for generalized multi-granulation neighborhood dominant rough sets, based on a matrix form, in an intuitionistic fuzzy ordered information table. We first define support and inclusion functions to construct the model of generalized multi-granulation neighborhood dominant rough sets. Additionally, we analyze the dynamic update process in which objects are added or removed in matrix form. Corresponding dynamic update algorithms are proposed based on generalized multi-granulation neighborhood dominant rough sets. Finally, to validate the effectiveness of the matrix-based dynamic approximation update algorithm, eight UCI datasets are used to perform experiments. The results verify that our matrix-based dynamic update algorithm is effective in approximating updates for dynamic intuitionistic fuzzy ordered information datasets.
Published Version
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