Transactions on Rough Sets XV [electronic resource] / edited by James F. Peters, Andrzej Skowron.
Contributor(s): Peters, James F [editor.]
| Skowron, Andrzej [editor.] | SpringerLink (Online service).
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BookSeries: Transactions on Rough Sets: 7255Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Edition: 1st ed. 2012.Description: IX, 181 p. 54 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642319037.Subject(s): Pattern recognition systems | Artificial intelligence | Machine theory | Numerical analysis | Computer vision | Information storage and retrieval systems | Automated Pattern Recognition | Artificial Intelligence | Formal Languages and Automata Theory | Numerical Analysis | Computer Vision | Information Storage and RetrievalAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.4 Online resources: Click here to access online
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Springer Nature eBookSummary: 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 XV offers a number of research streams that have grown out of the seminal work by Zdzislaw Pawlak. The 4 contributions included in this volume presents a rough set approach in machine learning; the introduction of multi-valued near set theory; the advent of a complete system that supports a rough-near set approach to digital image analysis; and an exhaustive study of the mathematics of vagueness.
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 XV offers a number of research streams that have grown out of the seminal work by Zdzislaw Pawlak. The 4 contributions included in this volume presents a rough set approach in machine learning; the introduction of multi-valued near set theory; the advent of a complete system that supports a rough-near set approach to digital image analysis; and an exhaustive study of the mathematics of vagueness.
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