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Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas

In Honor of Hung T. Nguyen's 75th Birthday

  • Vladik Kreinovich
Book

Part of the Studies in Computational Intelligence book series (SCI, volume 892)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Donald Bamber
    Pages 15-29
  3. G. Bezhanishvili, J. Harding
    Pages 31-46
  4. Bernadette Bouchon-Meunier
    Pages 47-54
  5. William M. Briggs
    Pages 55-65
  6. Didier Dubois, Luc Jaulin, Henri Prade
    Pages 101-109
  7. Emmanuel Haven
    Pages 127-132
  8. Nadipuram R. Prasad
    Pages 193-218

About this book

Introduction

Mainly focusing on processing uncertainty, this book presents state-of-the-art techniques and demonstrates their use in applications to econometrics and other areas. Processing uncertainty is essential, considering that computers – which help us understand real-life processes and make better decisions based on that understanding – get their information from measurements or from expert estimates, neither of which is ever 100% accurate. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described using fuzzy techniques. Therefore, it is important to master both techniques for processing data. This book is highly recommended for researchers and students interested in the latest results and challenges in uncertainty, as well as practitioners who want to learn how to use the corresponding state-of-the-art techniques. 

Keywords

Fuzzy Systems Fuzziness Data Processing Uncertainty Hung T. Nguyen

Editors and affiliations

  • Vladik Kreinovich
    • 1
  1. 1.Department of Computer ScienceUniversity of Texas at El PasoEl PasoUSA

Bibliographic information

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