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Extremal fuzzy dynamic systems : theory and applications /

In this book the author presents a new approach to the study of weakly structurable dynamic systems. It differs from other approaches by considering time as a source of fuzzy uncertainty in dynamic systems. It begins with a thorough introduction, where the general research domain, the problems, and...

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Bibliographic Details
Main Author: Sirbiladze, Gia
Format: Printed Book
Language:English
Published: New York: Springer, 2013.
Series:IFSR international series on systems science and engineering ; v.28.
Subjects:
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020 |a 9781461442493 (alk. paper) 
020 |a 1461442494 (alk. paper) 
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100 1 |a Sirbiladze, Gia. 
245 1 0 |a Extremal fuzzy dynamic systems :  |b theory and applications /  |c Gia Sirbiladze. 
260 |a New York:  |b Springer,  |c 2013. 
300 |a xxii, 400 pages :  |b illustrations ;  |c 24 cm. 
490 1 |a IFSR international series on systems science and engineering,  |x 1574-0463 ;  |v v. 28 
504 |a Includes bibliographical references (pages 375-382) and index. 
505 0 |a 1. Introduction -- 2. Monotone measure probability representations and weighted fuzzy statistics -- 3. Extended extremal monotone measures -- 4. Extended extremal monotone measures on composition products of measurable spaces -- 5. Modeling of extremal and controllable extremal fuzzy processes -- 6. Identification of fuzzy-Integral models of extremal fuzzy processes -- 7. Optimization of continuous controllable extremal fuzzy processes and the choice of decisions -- 8. Problems of states estimation (filtration) of extremal fuzzy processes -- 9. Summary of chapters 3-8 -- 10. Application of the discrete possibilistic model of the EFDS to the evaluation of expert knowledge streams -- 11. Forecasting decreasing financial risk of the Georgia-based organization Industria Kiri ltd. by a finite model of a possibilistic dynamic system -- 12. On the genetic algorithms approach and software library. 
520 |a In this book the author presents a new approach to the study of weakly structurable dynamic systems. It differs from other approaches by considering time as a source of fuzzy uncertainty in dynamic systems. It begins with a thorough introduction, where the general research domain, the problems, and ways of their solutions are discussed. The book then progresses systematically by first covering the theoretical aspects before tackling the applications. In the application section, a software library is described, which contains discrete EFDS identification methods elaborated during fundamental research of the book. Extremal fuzzy dynamic systems will be of interest to theoreticians interested in modeling fuzzy processes, to researchers who use fuzzy statistics, as well as practitioners from different disciplines whose research interests include abnormal, extreme and monotone processes in nature and society. Graduate students could also find this book useful -- 
650 0 |a Fuzzy decision making. 
650 0 |a Fuzzy systems. 
650 0 |a Artificial intelligence. 
650 7 |a Artificial intelligence.  |2 fast 
650 7 |a Fuzzy decision making.  |2 fast 
650 7 |a Fuzzy systems.  |2 fast 
942 |c BK 
830 0 |a IFSR international series on systems science and engineering ;  |v v.28. 
906 |a 7  |b cbc  |c copycat  |d 2  |e epcn  |f 20  |g y-gencatlg 
955 |b rl09 2014-10-20 z-processor  |i rl09 2014-10-21 ; to CALM 
955 |a pc17 2012-07-16  |a xh00 2012-12-21 to STM 
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