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© 2017

The Fundamentals of Computational Intelligence: System Approach

Book

Part of the Studies in Computational Intelligence book series (SCI, volume 652)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Mikhail Z. Zgurovsky, Yuriy P. Zaychenko
    Pages 1-37
  3. Mikhail Z. Zgurovsky, Yuriy P. Zaychenko
    Pages 39-79
  4. Mikhail Z. Zgurovsky, Yuriy P. Zaychenko
    Pages 81-131
  5. Mikhail Z. Zgurovsky, Yuriy P. Zaychenko
    Pages 179-219
  6. Mikhail Z. Zgurovsky, Yuriy P. Zaychenko
    Pages 261-307
  7. Mikhail Z. Zgurovsky, Yuriy P. Zaychenko
    Pages 309-348
  8. Back Matter
    Pages 373-375

About this book

Introduction

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 analyzedThe 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.

 

Keywords

Computational Intelligence Fuzzy Logic Systems Fuzzy Neural Networks GMDH Neural Networks

Authors and affiliations

  1. 1.National Technical University of UkraineKievUkraine
  2. 2.Institute for Applied System AnalysisNat.Tech.Univ.of Ukraine"Kiev Poly Inst"KievUkraine

Bibliographic information

  • Book Title The Fundamentals of Computational Intelligence: System Approach
  • Authors Mikhail Z. Zgurovsky
    Yuriy P. Zaychenko
  • Series Title Studies in Computational Intelligence
  • Series Abbreviated Title Studies Comp.Intelligence
  • DOI https://doi.org/10.1007/978-3-319-35162-9
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-35160-5
  • Softcover ISBN 978-3-319-81739-2
  • eBook ISBN 978-3-319-35162-9
  • Series ISSN 1860-949X
  • Series E-ISSN 1860-9503
  • Edition Number 1
  • Number of Pages XX, 375
  • Number of Illustrations 73 b/w illustrations, 70 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
  • Buy this book on publisher's site

Reviews

“The book under review is a well-written volume mainly addressing fuzzy systems. … The applications explored are geared heavily towards finance, and as such this book is probably a good introduction to CI for a graduate level course in economics, finance or social sciences. … Overall, this is a nice book, with a refreshing Eastern European style of writing … .” (Sandro Skansi, Mathematical Reviews, August, 2018)

“The book describes the mathematical equations, inequalities, and functions that can be used to calculate some results and achieve some data analysis objectives. … The book is interesting for researchers working on economic, financial, and societal phenomena, but it requires a deep understanding the underlying mathematical techniques. The book may be useful for researchers of computational intelligence because it contains a comprehensive set of algorithms and their mathematical descriptions.” (Bálint Molnár, Computing Reviews, April, 2017)