Granular Computing: At the Junction of Rough Sets and Fuzzy Sets, Rafael Bello; Rafael Falc?n; Witold Pedrycz

Автор: Dominik Slezak; JingTao Yao; James F. Peters; Wojc
Название: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing
ISBN: 3540286608 ISBN-13(EAN): 9783540286608
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Contains papers from the proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, held in Regina, Canada in August/September 2005 in 2 volumes.

Автор: Sanchez
Название: Type-2 Fuzzy Granular Models
ISBN: 3319412876 ISBN-13(EAN): 9783319412870
Издательство: Springer
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Цена: 7685.00 р.
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Описание: A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via multiple approaches, such as Coefficient of Variation, principle of justifiable granularity, uncertainty-based information concept, and numerical evidence based.

Автор: Kacprzyk
Название: Granular, Soft and Fuzzy Approaches for Intelligent Systems
ISBN: 3319403125 ISBN-13(EAN): 9783319403120
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book offers a comprehensive report on the state-of-the art in the broadly-intended field of “intelligent systems”. After introducing key theoretical issues, it describes a number of promising models for data and system analysis, decision making, and control. It discusses important theories, including possibility theory, the Dempster-Shafer theory, the theory of approximate reasoning, as well as computing with words, together with novel applications in various areas, such as information aggregation and fusion, linguistic data summarization, participatory learning, systems modeling, and many others. By presenting the methods in their application contexts, the book shows how granular computing, soft computing and fuzzy logic techniques can provide novel, efficient solutions to real-world problems. It is dedicated to Professor Ronald R. Yager for his great scientific and scholarly achievements, and for his long-lasting service to the fuzzy logic, and the artificial and computational intelligence communities. It has been motivated by the authors’ appreciation of his original thinking and groundbreaking ideas, with a special thought to his valuable research on the computerized implementation of various aspects of human cognition for decision-making and problem-solving.

Автор: Chien-Chung Chan; Jerzy W. Grzymala-Busse; Wojciec
Название: Rough Sets and Current Trends in Computing
ISBN: 3540884238 ISBN-13(EAN): 9783540884231
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Constitutes the refereed proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2008, held in Akron, OH, USA, in October 2008. This book presents the papers that are organized in topical sections on logical and mathematical foundations, data analysis, data mining, and decision support systems.

Автор: Dominik Slezak; Marcin Szczuka; Ivo Duentsch; Yiyu
Название: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing
ISBN: 3540286535 ISBN-13(EAN): 9783540286530
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Part of a two volume set, this title includes information related to rough set approximations, rough-algebraic foundations, feature selection and reduction, rough-probabilistic approaches, rough-fuzzy hybridization, fuzzy methods in data analysis, evolutionary computing, machine learning, probabilistic network models, granular computing, and more.

Автор: Hiroshi Sakai; Mihir Chakraborty; Aboul-Ella Hassa
Название: Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
ISBN: 3642106455 ISBN-13(EAN): 9783642106453
Издательство: Springer
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Цена: 14673.00 р.
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Описание: This book constitutes the refereed proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2009, held in Delhi, India in December 2009 in conjunction with the Third International Conference on Pattern Recognition and Machine Intelligence, PReMI 2009.