04859nam a22005055i 4500 11863 11863 978-3-319-35162-9 DE-He213 20211208102312.0 160701s2017 gw | s |||| 0|eng d 9783319351629 AIKTC-KRRC ENG UYQ bicssc TEC009000 bisacsh UYQ thema 006.3 23 Zgurovsky, Mikhail Z. author. aut http://id.loc.gov/vocabulary/relators/aut Fundamentals of Computational Intelligence: System Approach [electronic resource] / 1st ed. 2017. Cham : Springer International Publishing : Imprint: Springer, 2017. XX, 375 p. 143 illus., 70 illus. in color. Card Paper text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Studies in Computational Intelligence, 1860-949X ; 652 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. . Computer Engineering 4622 Computational Intelligence. Artificial Intelligence. Zaychenko, Yuriy P. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) Springer Nature eBook Printed edition: 9783319351605 Printed edition: 9783319351612 Printed edition: 9783319817392 Studies in Computational Intelligence, 1860-949X ; 652 https://doi.org/10.1007/978-3-319-35162-9 Click here to access eBook in Springer Nature platform. (Within Campus only.) EBOOKS ddc