Covering-based rough sets process data organized by a covering of the universe. A soft set is a parameterized family of subsets of the universe. Both theories can deal with the uncertainties of data. Soft sets have no...Covering-based rough sets process data organized by a covering of the universe. A soft set is a parameterized family of subsets of the universe. Both theories can deal with the uncertainties of data. Soft sets have not any restrictions on the approximate description of the object,and they might form a covering of the universe. From this viewpoint,we establish a connection between these two theories. Specifically,we propose a complementary parameter for this purpose. With this parameter,the soft covering approximation space is established and the two theories are bridged. Furthermore,we study some relations between the covering and the soft covering approximation space and obtain some significant results. Finally,we define a notion of combine parameter which can help us to simplify the set of parameters and reduce the storage requirement of a soft covering approximation space.展开更多
The authors study the covering rough sets by topological methods. They combine the covering rough sets and topological spaces by means of defining some new types of spaces called covering rough topological (CRT) space...The authors study the covering rough sets by topological methods. They combine the covering rough sets and topological spaces by means of defining some new types of spaces called covering rough topological (CRT) spaces based on neighbourhoods or complementary neighbourhoods. As the separation axioms play a fundamental role in general topology, they introduce all these axioms into covering rough set theories and thoroughly study the equivalent conditions for every separation axiom in several CRT spaces. They also investigate the relationships between the separation axioms in these special spaces and reveal these relationships through diagrams in different CRT spaces.展开更多
The coveting rough sets theory is a generalization of traditional rough set theory, and can also describe information with incompleteness and fuzziness in information systems. In this paper, we first provide the defin...The coveting rough sets theory is a generalization of traditional rough set theory, and can also describe information with incompleteness and fuzziness in information systems. In this paper, we first provide the definitions of several upper and lower covering approximation operators on the covering approximation space. Then, we study the properties of these operators. Finally, we propose the mutual relations between approximation operators and similar relations of the operator （ I ） based on the covering rough sets.展开更多
Covering rough sets are improvements of traditional rough sets by considering cover of universe instead of partition.In this paper,we develop several measures based on evidence theory to characterize covering rough se...Covering rough sets are improvements of traditional rough sets by considering cover of universe instead of partition.In this paper,we develop several measures based on evidence theory to characterize covering rough sets.First,we present belief and plausibility functions in covering information systems and study their properties.With these measures we characterize lower and upper approximation operators and attribute reductions in covering information systems and decision systems respectively.With these discussions we propose a basic framework of numerical characterizations of covering rough sets.展开更多
Rough set theory is a technique of granular computing. In this paper, we study a type of generalized rough sets based on covering. There are several literatures[1,40-43] exploring covering-based rough sets. Our focus ...Rough set theory is a technique of granular computing. In this paper, we study a type of generalized rough sets based on covering. There are several literatures[1,40-43] exploring covering-based rough sets. Our focus of this paper is on the dualities in rough operations.展开更多
This paer gives an artificial network(RCSN)combining rough set theory and covering design algorithm,which reduces condition attribute using rough set theory and designs the structure of neural network with covering de...This paer gives an artificial network(RCSN)combining rough set theory and covering design algorithm,which reduces condition attribute using rough set theory and designs the structure of neural network with covering de-sign algorithm. An instance shows this kind of network has the advantages of fast computation and high accuracy ;themethod also can cut down the occupying of memory and the cost of data collecting.展开更多
基金supported by National Natural Science Foundation of China under Grant No. 60873077/F020107the Science Research Project of Zhangzhou Normal University under Grant No. SK09002
文摘Covering-based rough sets process data organized by a covering of the universe. A soft set is a parameterized family of subsets of the universe. Both theories can deal with the uncertainties of data. Soft sets have not any restrictions on the approximate description of the object,and they might form a covering of the universe. From this viewpoint,we establish a connection between these two theories. Specifically,we propose a complementary parameter for this purpose. With this parameter,the soft covering approximation space is established and the two theories are bridged. Furthermore,we study some relations between the covering and the soft covering approximation space and obtain some significant results. Finally,we define a notion of combine parameter which can help us to simplify the set of parameters and reduce the storage requirement of a soft covering approximation space.
文摘The authors study the covering rough sets by topological methods. They combine the covering rough sets and topological spaces by means of defining some new types of spaces called covering rough topological (CRT) spaces based on neighbourhoods or complementary neighbourhoods. As the separation axioms play a fundamental role in general topology, they introduce all these axioms into covering rough set theories and thoroughly study the equivalent conditions for every separation axiom in several CRT spaces. They also investigate the relationships between the separation axioms in these special spaces and reveal these relationships through diagrams in different CRT spaces.
基金The National Natural Science Foundation of China(No.60474022)
文摘The coveting rough sets theory is a generalization of traditional rough set theory, and can also describe information with incompleteness and fuzziness in information systems. In this paper, we first provide the definitions of several upper and lower covering approximation operators on the covering approximation space. Then, we study the properties of these operators. Finally, we propose the mutual relations between approximation operators and similar relations of the operator （ I ） based on the covering rough sets.
基金supported by a grant of NSFC(70871036)a grant of National Basic Research Program of China(2009CB219801-3)
文摘Covering rough sets are improvements of traditional rough sets by considering cover of universe instead of partition.In this paper,we develop several measures based on evidence theory to characterize covering rough sets.First,we present belief and plausibility functions in covering information systems and study their properties.With these measures we characterize lower and upper approximation operators and attribute reductions in covering information systems and decision systems respectively.With these discussions we propose a basic framework of numerical characterizations of covering rough sets.
文摘Rough set theory is a technique of granular computing. In this paper, we study a type of generalized rough sets based on covering. There are several literatures[1,40-43] exploring covering-based rough sets. Our focus of this paper is on the dualities in rough operations.
文摘This paer gives an artificial network(RCSN)combining rough set theory and covering design algorithm,which reduces condition attribute using rough set theory and designs the structure of neural network with covering de-sign algorithm. An instance shows this kind of network has the advantages of fast computation and high accuracy ;themethod also can cut down the occupying of memory and the cost of data collecting.
