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Titlebook: Rough Sets and Current Trends in Computing; Third International James J. Alpigini,James F. Peters,Ning Zhong Conference proceedings 2002 S

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書目名稱Rough Sets and Current Trends in Computing
副標題Third International
編輯James J. Alpigini,James F. Peters,Ning Zhong
視頻videohttp://file.papertrans.cn/832/831903/831903.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Rough Sets and Current Trends in Computing; Third International  James J. Alpigini,James F. Peters,Ning Zhong Conference proceedings 2002 S
描述This volume contains the papers selected for presentation at the Third Inter- tional Conference on Rough Sets and Current Trends in Computing (RSCTC 2002) held at Penn State Great Valley, Malvern, Pennsylvania, U.S.A., 14–16 October 2002. Rough set theoryand its applications constitute a branch of soft computing that has exhibited a signi?cant growth rate during recent years. RSCTC 2002 provided a forum for exchanging ideas among manyresearchers in the rough set communityand in various areas of soft computing and served as a stimulus for mutual understanding and cooperation. In recent years, there have been a number of advances in rough set theoryand applications. Hence, we have witnessed a growing number of international workshops on rough sets and their applications. In addition, it should be observed that one of the beauties of rough sets and the rough set philosophyis that it tends to complement and reinforce research in manytraditional research areas and applications. This is the main reason that manyinternational conferences are now including rough sets into the list of topics.
出版日期Conference proceedings 2002
關鍵詞Classifier Systems; Evolutionary Computing; Fuzzy Sets; Genetic Algorithms; Granular Computing; Knowledge
版次1
doihttps://doi.org/10.1007/3-540-45813-1
isbn_softcover978-3-540-44274-5
isbn_ebook978-3-540-45813-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2002
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Reasoning about Information Granules Based on Rough Logic interpreted in the context of rough set theory. Rough logic is defined over a given information system IS=(U,A). The propositions (or predicates) of this logic are logical formulas defined by attributes in IS. The semantics of such propositions is defined in the context of subsets of the universe U.
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A Rough Set Framework for Learning in a Directed Acyclic Graphenes) are organized in a directed acyclic graph (DAG). Standard learning methods such a Rough Sets assume that these classes are unrelated, and cannot handle this problem properly. To this end, we introduce an extended rough set framework with several new operators. We show how these operators can be used in an new learning algorithm.
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Fuzzy Sets, Multi-valued Mappings, and Rough SetsIt is shown that there is a natural transformation of Dempster’s multi-valued mapping and Pawlak’s rough sets and vice-versa. Furthermore, Dempster’s schema is modified and restricted by Turksen in a particular manner to generate interval-valued Type 2 fuzzy sets. This is named Dempster-Turksen schema.
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978-3-540-44274-5Springer-Verlag Berlin Heidelberg 2002
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