Transactions on Rough Sets XVII [electronic resource] / edited by James F. Peters, Andrzej Skowron.
Contributor(s): Peters, James F [editor.] | Skowron, Andrzej [editor.] | SpringerLink (Online service).
Material type: BookSeries: Transactions on Rough Sets: 8375Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Edition: 1st ed. 2014.Description: X, 294 p. 44 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642547560.Subject(s): Pattern recognition systems | Numerical analysis | Artificial intelligence | Machine theory | Automated Pattern Recognition | Numerical Analysis | Artificial Intelligence | Formal Languages and Automata TheoryAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.4 Online resources: Click here to access onlineThree-Valued Logics, Uncertainty Management and Rough Sets -- Standard Errors of Indices in Rough Set Data Analysis -- Proximity System: A Description-Based System for Quantifying the Nearness or Apartness of Visual Rough Sets -- Rough Sets and Matroids -- An Efficient Approach for Fuzzy Decision Reduct Computation -- Rough Sets in Economy and Finance -- Algorithms for Similarity Relation Learning from High Dimensional Data.
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XVII is a continuation of a number of research streams which have grown out of the seminal work by Zdzislaw Pawlak during the first decade of the 21st century. The research streams represented in the papers cover both theory and applications of rough, fuzzy and near sets as well as their combinations.
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