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The Fundamentals of Computational Intelligence: System Approach

  • Mikhail Z. Zgurovsky
  • Yuriy P. Zaychenko

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

  • Mikhail Z. Zgurovsky
    • 1
  • Yuriy P. Zaychenko
    • 2
  1. 1.National Technical University of UkraineKievUkraine
  2. 2.Institute for Applied System AnalysisNat.Tech.Univ.of Ukraine"Kiev Poly Inst"KievUkraine

Bibliographic information

  • 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
  • Print ISBN 978-3-319-35160-5
  • Online ISBN 978-3-319-35162-9
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site