Titlebook: Rough Sets and Intelligent Systems Paradigms; International Confer Marzena Kryszkiewicz,James F. Peters,Andrzej Skowr Conference proceeding

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书目名称Rough Sets and Intelligent Systems Paradigms影响因子(影响力)




书目名称Rough Sets and Intelligent Systems Paradigms影响因子(影响力)学科排名




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书目名称Rough Sets and Intelligent Systems Paradigms网络公开度学科排名




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书目名称Rough Sets and Intelligent Systems Paradigms被引频次学科排名




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书目名称Rough Sets and Intelligent Systems Paradigms年度引用学科排名




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书目名称Rough Sets and Intelligent Systems Paradigms读者反馈学科排名

牛马之尿

Gesture

多余

Granular Computing and Rough Set Theory whose values are labeled with words drawn from a natural language. For example, if . is temperature, then 101.3 is a singular value of temperature, while ”high” is a granular (linguistic) value of temperature.

注射器

Rough Sets and Vague SetsThe considerations intend to take into account a classical approach to reasoning, based on vague premises, and suggest finding a logic of vague sentences as a non-classical logic in which all counterparts of tautologies of classical logic are laws.

FRET

Certain, Generalized Decision, and Membership Distribution Reducts Versus Functional Dependencies inve that, unlike in the case of complete systems, the reducts in incomplete systems are not guaranteed to be minimal sets of conditional attributes that functionally determine respective modifications of the decision attribute.

investigate

暂时休息

Dependencies in Structures of Decision Tablesion of the Pawlak’s measure of the dependency between attributes and the expected certainty gain measure. The expected certainty gain measure reflects the subtle grades of probabilistic dependence of events. The measures are reviewed and it is shown how they can be extended to dependencies existing in hierarchical structures of decision tables.

Liability

Allergic

Dominance-Based Rough Set Approach to Reasoning About Ordinal Datauniverse, and about monotonic relationships between these evaluations, e.g. “the larger the mass and the smaller the distance, the larger the gravity” or “the greater the debt of a firm, the greater its risk of failure”. Such a knowledge is typical for data describing various phenomena, and for data