The Fundamentals of Computational Intelligence: System Approach (Studies in Computational Intelligence)
暫譯: 計算智慧的基本原理:系統方法(計算智慧研究)

Mikhail Z. Zgurovsky

  • 出版商: Springer
  • 出版日期: 2018-06-07
  • 售價: $6,930
  • 貴賓價: 9.5$6,584
  • 語言: 英文
  • 頁數: 396
  • 裝訂: Paperback
  • ISBN: 3319817396
  • ISBN-13: 9783319817392
  • 海外代購書籍(需單獨結帳)

商品描述

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.

 

商品描述(中文翻譯)

這本專著專門系統性地介紹計算智能(Computational Intelligence, CI)的主要趨勢、技術和方法。書中特別關注一項重要的CI技術——模糊邏輯(Fuzzy Logic, FL)系統和模糊神經網絡(Fuzzy Neural Networks, FNN)。考慮了不同類型的FNN,包括新類別的FNN——級聯新模糊神經網絡,並描述和分析了它們的訓練算法。書中探討了FNN在宏觀經濟學和股市預測中的應用。該書提出了在不確定性下的投資組合優化問題,提出了一種新理論的模糊投資組合優化,克服了馬可維茲(Markowitz)經典模型的缺陷,並應用於烏克蘭、俄羅斯和美國的股市投資組合優化。書中還提出了在不完整和模糊信息下預測企業破產風險的問題,以及基於模糊集理論和模糊神經網絡的新方法,並展示了其在破產風險預測中的應用結果,並與阿特曼(Altman)方法進行比較。

這本專著還專注於一種自組織的歸納建模方法——所謂的數據處理群體方法(Group Method of Data Handling, GMDH),該方法幾乎可以自動構建預測模型的結構。書中展示了GMDH在股市預測中的實驗研究結果。最後幾章專門討論進化建模(Evolutionary Modeling, EM)和遺傳算法(Genetic Algorithms)的理論和應用。

這本專著的特點是提供了大量實際案例,展示CI技術和方法在技術、經濟和金融領域解決實際問題中的應用,特別是在預測、分類、模式識別、投資組合優化和在不確定性下的破產風險預測等方面,這些案例由作者開發並首次在本書中發表。所有CI方法和算法都從一般系統的角度進行介紹,並分析其特性、優勢和缺點,使實務工作者能夠選擇最適合自己問題解決的方案。

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