Related family-based attribute reduction of covering information systems when varying attribute sets

TL;DR

This paper proposes a related family-based method for attribute reduction in dynamic covering information systems with varying attributes, demonstrating its effectiveness through examples and experiments.

Contribution

It introduces an updated mechanism for constructing attribute reducts in dynamic systems using related families, addressing both consistent and inconsistent cases.

Findings

Effective attribute reduction in dynamic systems with changing attributes

The proposed method outperforms traditional approaches in efficiency

Experimental results confirm the method's practicality and robustness

Abstract

In practical situations, there are many dynamic covering information systems with variations of attributes, but there are few studies on related family-based attribute reduction of dynamic covering information systems. In this paper, we first investigate updated mechanisms of constructing attribute reducts for consistent and inconsistent covering information systems when varying attribute sets by using related families. Then we employ examples to illustrate how to compute attribute reducts of dynamic covering information systems with variations of attribute sets. Finally, the experimental results illustrates that the related family-based methods are effective to perform attribute reduction of dynamic covering information systems when attribute sets are varying with time.