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Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications

  • Book
  • © 2021

Overview

Authors:
  1. József Dombi

    1. Institute of Informatics, University of Szeged, Szeged, Hungary

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    You can also search for this author in PubMed   Google Scholar

  2. Tamás Jónás

    1. Institute of Business Economics, Eötvös Loránd University, Budapest, Hungary

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Focuses on advances in the areas of soft computational and probabilistic methods
  • Discusses theoretical results and potential applications
  • Presents advances in probabilistic and fuzzy data scientific methods

Part of the book series: Studies in Computational Intelligence (SCI, volume 814)

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Table of contents (5 chapters)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. Belief, Probability and Plausibility

    • József Dombi, Tamás Jónás
    Pages 1-26

  3. \(\lambda \)-Additive and \(\nu \)-Additive Measures

    • József Dombi, Tamás Jónás
    Pages 27-83

  4. The Pliant Probability Distribution Family

    • József Dombi, Tamás Jónás
    Pages 85-134

  5. A Fuzzy Arithmetic-Based Time Series Model

    • József Dombi, Tamás Jónás
    Pages 135-165

  6. Likert Scale-Based Evaluations with Flexible Fuzzy Numbers

    • József Dombi, Tamás Jónás
    Pages 167-187
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Keywords

About this book

This book focuses on the advanced soft computational and probabilistic methods that the authors have published over the past few years. It describes theoretical results and applications, and  discusses how various uncertainty measures – probability, plausibility and belief measures – can be treated in a unified way. It also examines approximations of four notable probability distributions (Weibull, exponential, logistic and normal) using a unified probability distribution function, and presents a fuzzy arithmetic-based time series model that provides an easy-to-use forecasting technique. Lastly, it proposes flexible fuzzy numbers for Likert scale-based evaluations. Featuring methods that can be successfully applied in a variety of areas, including engineering, economics, biology and the medical sciences, the book offers useful guidelines for practitioners and researchers.   

Authors and Affiliations

  • Institute of Informatics, University of Szeged, Szeged, Hungary

    József Dombi

  • Institute of Business Economics, Eötvös Loránd University, Budapest, Hungary

    Tamás Jónás

Bibliographic Information

  • Book Title: Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications

  • Authors: József Dombi, Tamás Jónás

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-51949-0

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

  • Hardcover ISBN: 978-3-030-51948-3Published: 12 August 2020

  • Softcover ISBN: 978-3-030-51951-3Published: 13 August 2021

  • eBook ISBN: 978-3-030-51949-0Published: 11 August 2020

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XVII, 187

  • Number of Illustrations: 67 b/w illustrations

  • Topics: Data Engineering, Computational Intelligence

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