A study of \((I_{O}, O)\)-fuzzy rough sets using overlap functions in complete lattices
摘要
Rough set theory provides a formal mathematical framework for handling knowledge uncertainty in data mining. Its core components, the upper and lower approximation operators, represent fundamental concepts within the theory. Their study within lattice theory frameworks marks an important mathematical advancement. Simultaneously, overlap functions, which are non-associative binary aggregation functions contrasting with conventional t-norms, play a pivotal role in formulating fuzzy rough approximation operators. In light of these two pivotal factors, this work introduces