Overview
- Advanced research on possibility distributions and decisions
- Application of fuzzy logic, probability and possibility theory
- Written by leading experts in the fiel
Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 270)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
This book starts with the basic concepts of fuzzy sets and progresses through a normative view on possibility distributions and OWA operators in multiple criteria decisions.
Five applications (that all build on experience from solving complex real world problems) of possibility distributions to strategic decisions about closing/not closing a production plant using fuzzy real options, portfolio selection with imprecise future data, predictive probabilities and possibilities for risk assessment in grid computing, fuzzy ontologies for process industry, and design (and implementation) of mobile value services are presented and carefully discussed. It can be useful for researchers and students working in soft computing, real options, fuzzy decision making, grid computing, knowledge mobilization and mobile value services.
Similar content being viewed by others
Keywords
Table of contents (9 chapters)
-
Front Matter
-
Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Possibility for Decision
Book Subtitle: A Possibilistic Approach to Real Life Decisions
Authors: Christer Carlsson, Robert Fullér
Series Title: Studies in Fuzziness and Soft Computing
DOI: https://doi.org/10.1007/978-3-642-22642-7
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag GmbH Berlin Heidelberg 2011
Hardcover ISBN: 978-3-642-22641-0Published: 25 July 2011
Softcover ISBN: 978-3-642-27128-1Published: 27 November 2013
eBook ISBN: 978-3-642-22642-7Published: 25 July 2011
Series ISSN: 1434-9922
Series E-ISSN: 1860-0808
Edition Number: 1
Number of Pages: XI, 249
Topics: Computational Intelligence, Mathematical and Computational Engineering, Probability and Statistics in Computer Science