Expert Fuzzy Information Processing

This book deals with expert evaluation models in the form of semantic spaces with completeness and orthogonality properties (complete orthogonal semantic spaces). Theoretical and practical studies of some researchers have shown that these spaces describe expert evaluations most adequately, and as a...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Poleshchuk, Olga (Συγγραφέας), Komarov, Evgeniy (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
Σειρά:Studies in Fuzziness and Soft Computing, 268
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Poleshchuk, Olga.  |e author. 
245 1 0 |a Expert Fuzzy Information Processing  |h [electronic resource] /  |c by Olga Poleshchuk, Evgeniy Komarov. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2011. 
300 |a XVI, 240 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Studies in Fuzziness and Soft Computing,  |x 1434-9922 ;  |v 268 
505 0 |a Chapter 1. The basic concepts of the fuzzy sets theory -- Methods of expert information formalization based on complete orthogonal semantic spaces -- Methods of comparative and fuzzy cluster analysis of formalized information -- Model-building methods of the generalized characteristic expert evaluation models -- Ratings of objects -- Complete orthogonal semantic spaces in problems of the fuzzy regression analysis. 
520 |a This book deals with expert evaluation models in the form of semantic spaces with completeness and orthogonality properties (complete orthogonal semantic spaces). Theoretical and practical studies of some researchers have shown that these spaces describe expert evaluations most adequately, and as a result they were often included in more sophisticated models of intellectual systems for decision making and data analysis. Methods for constructing expert evaluation models of characteristics, comparative analysis of these models, studies of structural composition of their sets and constructing of generalized models are described. Models to obtain rating points for objects and groups of objects with qualitative and quantitative characteristics are presented. A number of regression models combining elements of classical and fuzzy regressions are presented. All methods and models developed by the authors and described in the book are illustrated with examples from various fields of human activities. This book meant for scientists in the field of computer science, expert systems, artificial intelligence and decision making; and also for engineers, post-graduate students and students who study the fuzzy set theory and its applications. 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Computational intelligence. 
650 1 4 |a Engineering. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
700 1 |a Komarov, Evgeniy.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642201240 
830 0 |a Studies in Fuzziness and Soft Computing,  |x 1434-9922 ;  |v 268 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-20125-7  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)