Please use this identifier to cite or link to this item: http://dlib.scu.ac.ir/handle/Hannan/64646
Title: The Fundamentals of Computational Intelligence: System Approach
Authors: Zgurovsky, Mikhail Z. ; author. ;;Zaychenko, Yuriy P. ; author. ;
subject: Engineering;Artificial Intelligence;Computational Intelligence;Engineering;Computational Intelligence. ;;Artificial Intelligence;Engineering;Artificial Intelligence;Computational Intelligence;Engineering;Computational Intelligence. ;;Artificial Intelligence
Year: 2017
place: Cham :
Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Studies in Computational Intelligence, ; 1860-949X ; ; 652 ;
Studies in Computational Intelligence, ; 1860-949X ; ; 652 ;
Abstract: This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms. The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution. . ;
Description: 

006.3 ; 23 ;

Tdig ; ALMA ;
Printed edition: ; The Fundamentals of Computational Intelligence: System Approach ; 9783319351605 ;
URI: http://46.100.53.162/handle/Ebook/155828
http://46.100.53.162/handle/Ebook/64646
ISBN: 9783319351629 ; 9783319351605 (Print) ;
Appears in Collections:مهندسی رباتیک

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Title: The Fundamentals of Computational Intelligence: System Approach
Authors: Zgurovsky, Mikhail Z. ; author. ;;Zaychenko, Yuriy P. ; author. ;
subject: Engineering;Artificial Intelligence;Computational Intelligence;Engineering;Computational Intelligence. ;;Artificial Intelligence;Engineering;Artificial Intelligence;Computational Intelligence;Engineering;Computational Intelligence. ;;Artificial Intelligence
Year: 2017
place: Cham :
Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Studies in Computational Intelligence, ; 1860-949X ; ; 652 ;
Studies in Computational Intelligence, ; 1860-949X ; ; 652 ;
Abstract: This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms. The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution. . ;
Description: 

006.3 ; 23 ;

Tdig ; ALMA ;
Printed edition: ; The Fundamentals of Computational Intelligence: System Approach ; 9783319351605 ;
URI: http://46.100.53.162/handle/Ebook/155828
http://46.100.53.162/handle/Ebook/64646
ISBN: 9783319351629 ; 9783319351605 (Print) ;
Appears in Collections:مهندسی رباتیک

Files in This Item:
File Description SizeFormat 
9783319351629.pdf9.36 MBAdobe PDFThumbnail
Preview File
Title: The Fundamentals of Computational Intelligence: System Approach
Authors: Zgurovsky, Mikhail Z. ; author. ;;Zaychenko, Yuriy P. ; author. ;
subject: Engineering;Artificial Intelligence;Computational Intelligence;Engineering;Computational Intelligence. ;;Artificial Intelligence;Engineering;Artificial Intelligence;Computational Intelligence;Engineering;Computational Intelligence. ;;Artificial Intelligence
Year: 2017
place: Cham :
Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Studies in Computational Intelligence, ; 1860-949X ; ; 652 ;
Studies in Computational Intelligence, ; 1860-949X ; ; 652 ;
Abstract: This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms. The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution. . ;
Description: 

006.3 ; 23 ;

Tdig ; ALMA ;
Printed edition: ; The Fundamentals of Computational Intelligence: System Approach ; 9783319351605 ;
URI: http://46.100.53.162/handle/Ebook/155828
http://46.100.53.162/handle/Ebook/64646
ISBN: 9783319351629 ; 9783319351605 (Print) ;
Appears in Collections:مهندسی رباتیک

Files in This Item:
File Description SizeFormat 
9783319351629.pdf9.36 MBAdobe PDFThumbnail
Preview File