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Table of contents (27 chapters)
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Front Matter
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Applications of the Rough Sets Approach to Intelligent Decision Support
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Front Matter
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Comparison with Related Methodologies
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Front Matter
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Keywords
About this book
Knowledge is understood here as an ability to classify objects. Objects being in the same class are indiscernible by means of attributes and form elementary building blocks (granules, atoms). In particular, the granularity of knowledge causes that some notions cannot be expressed precisely within available knowledge and can be defined only vaguely. In the rough sets theory created by Z. Pawlak each imprecise concept is replaced by a pair of precise concepts called its lower and upper approximation. These approximations are fundamental tools and reasoning about knowledge.
The rough sets philosophy turned out to be a very effective, new tool with many successful real-life applications to its credit.
It is worthwhile stressing that no auxiliary assumptions are needed about data, like probability or membership function values, which is its great advantage.
The present book reveals a wide spectrum of applications of the rough set concept, giving the reader the flavor of, and insight into, the methodology of the newly developed disciplines. Although the book emphasizes applications, comparison with other related methods and further developments receive due attention.
Editors and Affiliations
Bibliographic Information
Book Title: Intelligent Decision Support
Book Subtitle: Handbook of Applications and Advances of the Rough Sets Theory
Editors: Roman Słowiński
Series Title: Theory and Decision Library D:
DOI: https://doi.org/10.1007/978-94-015-7975-9
Publisher: Springer Dordrecht
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media B.V. 1992
Hardcover ISBN: 978-0-7923-1923-8Published: 31 August 1992
Softcover ISBN: 978-90-481-4194-4Published: 15 December 2010
eBook ISBN: 978-94-015-7975-9Published: 09 March 2013
Edition Number: 1
Number of Pages: XVII, 473
Topics: Artificial Intelligence, Operations Research/Decision Theory, Mathematical Logic and Foundations