Rough Sets: Selected Methods and Applications in Management and Engineering (Advanced Information and Knowledge Processing)

Peters, Georg (Editor) / Yao, Yiyu (Editor) / Slezak, Dominik (Editor) / Lingras, Pawan (Editor)

ISBN 10: 1447169166 / ISBN 13: 9781447169161

Editore: Springer, 2016

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reprint edition. 214 pages. 9.25x6.10x0.51 inches. In Stock.

Codice articolo zk1447169166

Dati bibliografici

• Titolo: Rough Sets: Selected Methods and Applications in Management and Engineering (Advanced Information and Knowledge Processing)
• Editore: Springer
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 1447169166
• ISBN 13: 9781447169161
• Rilegatura: Paperback
• Condizione: Brand New
• Peso: 0,47 chilogrammi

Descrizione articolo

Riassunto

Introduced in the early 1980s, Rough Set Theory has become an important part of soft computing in the last 25 years. This book provides a practical, context-based analysis of rough set theory, with each chapter exploring a real-world application of Rough Sets.

Dalla quarta di copertina

Rough Set Theory was introduced in the early 1980's. In the last quarter century it has become an important part of soft computing and has proved its relevance in many real-world applications.

Initially most articles on Rough Sets were centered on theory, currently though the focus of the research has shifted to practical usage of mathematical advances. With this in mind this book is written for researchers at universities wanting to use Rough Sets to solve real-world problems and needing guidance on how best to describe their ideas in ways not only understandable to industry readers, but also for managers looking for methods to improve their businesses, and researchers in industrial laboratories and think-tanks investigating new methods to enhance the efficiency of their solutions.

Rough Sets: Selected Methods and Applications in Management and Engineering is unique in its focus on use cases backed by sound theory in contrast to the presentation of a theory applied to a problem. A diverse range of applications, including coverage of methods in data analysis, decision support as well as management and engineering, demonstrates the great potential of Rough Sets in almost any domain.