Discrete mathematics for computer science
Discrete mathematics for computer science
Reduction and axiomization of covering generalized rough sets
Information Sciences: an International Journal
Topological approaches to covering rough sets
Information Sciences: an International Journal
The algebraic structures of generalized rough set theory
Information Sciences: an International Journal
Relationship between generalized rough sets based on binary relation and covering
Information Sciences: an International Journal
Rough sets approach to symbolic value partition
International Journal of Approximate Reasoning
A hierarchical model for test-cost-sensitive decision systems
Information Sciences: an International Journal
Relationship among basic concepts in covering-based rough sets
Information Sciences: an International Journal
MGRS: A multi-granulation rough set
Information Sciences: an International Journal
Constructive and algebraic methods of the theory of rough sets
Information Sciences: an International Journal
Positive approximation: An accelerator for attribute reduction in rough set theory
Artificial Intelligence
Poset approaches to covering-based rough sets
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Binary relation based rough sets
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Rough fuzzy MLP: knowledge encoding and classification
IEEE Transactions on Neural Networks
Covering based rough set approximations
Information Sciences: an International Journal
Quantitative analysis for covering-based rough sets through the upper approximation number
Information Sciences: an International Journal
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Rough set theory provides a systematic way for rule extraction, attribute reduction and knowledge classification in information systems. Some measurements are important in rough sets. For example, information entropy, knowledge dependency are useful in attribute reduction algorithms. This paper proposes the concepts of the lower and upper covering numbers to establish measurements in covering-based rough sets which are generalizations of rough sets. With covering numbers, we establish a distance structure, two semilattices and a lattice for covering-based rough sets. The new concepts are helpful in studying covering-based rough sets from topological and algebraical viewpoints.