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Transactions on Rough Sets XVII / edited by James F. Peters, Andrzej Skowron.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Transactions on Rough Sets, 1861-2067 ; 8375
- Language:
- English
- Subjects (All):
- Pattern recognition systems.
- Numerical analysis.
- Artificial intelligence.
- Machine theory.
- Automated Pattern Recognition.
- Numerical Analysis.
- Artificial Intelligence.
- Formal Languages and Automata Theory.
- Local Subjects:
- Automated Pattern Recognition.
- Numerical Analysis.
- Artificial Intelligence.
- Formal Languages and Automata Theory.
- Physical Description:
- 1 online resource (X, 294 pages) : 44 illustrations
- Edition:
- 1st ed. 2014.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
- System Details:
- text file PDF
- Summary:
- 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.
- Contents:
- Three-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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-642-54756-0
- 9783642547560
- Access Restriction:
- Restricted for use by site license.
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