20102010 International Conference on Educational and Network TechnologyRequires access

Rough data and applications of rough data law

Chang-Jing Lu, Qiu Jinming, Shi Kai-quan

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Abstract

S-rough sets (singular rough sets) theory was proposed by improving Z. Pawlak rough sets theory. S-rough sets have dynamic characteristics, since it is defined by R-element equivalence class [x] which has dynamic characteristic. The concept of rough data was presented by employing S-rough sets, and rough data has dynamic characteristic, furthermore, the rough data law generation is given. Based on the concepts above, the generation theorem and the reversion theorem of rough data law, the recognition criterion of rough data law, and the discernible theorem of rough data law were given, finally the applications of rough data law in risk investment system are presented.

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S-rough sets (singular rough sets) theory was proposed by improving Z. Pawlak rough sets theory. S-rough sets have dynamic characteristics, since it is defined by R-element equivalence class [x] which has dynamic characteristic. The concept of rough data was presented by employing S-rough sets, and rough data has dynamic characteristic, furthermore, the rough data law generation is given. Based on the concepts above, the generation theorem and the reversion theorem of rough data law, the recognition criterion of rough data law, and the discernible theorem of rough data law were given, finally the applications of rough data law in risk investment system are presented.

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Available abstract

S-rough sets (singular rough sets) theory was proposed by improving Z. Pawlak rough sets theory. S-rough sets have dynamic characteristics, since it is defined by R-element equivalence class [x] which has dynamic characteristic. The concept of rough data was presented by employing S-rough sets, and rough data has dynamic characteristic, furthermore, the rough data law generation is given. Based on the concepts above, the generation theorem and the reversion theorem of rough data law, the recognition criterion of rough data law, and the discernible theorem of rough data law were given, finally the applications of rough data law in risk investment system are presented.

Key concepts: Rough set, Equivalence class (music), Mathematics, Dominance-based rough set approach, Equivalence (formal languages), Data mining, Computer science, Pure mathematics

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