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Fuzzy Probabilities

New Approach and Applications

  • Book
  • © 2003

Overview

Authors:
  1. James J. Buckley

    1. Mathematics Department, University of Alabama at Birmingham, Birmingham, USA

    View author publications

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  • New method of dealing with imprecise probabilities, most of which not published before
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 115)

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-xi
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  2. Introduction

    • James J. Buckley
    Pages 1-6

  3. Fuzzy Sets

    • James J. Buckley
    Pages 7-30

  4. Fuzzy Probability Theory

    • James J. Buckley
    Pages 31-49

  5. Discrete Fuzzy Random Variables

    • James J. Buckley
    Pages 51-60

  6. Fuzzy Queuing Theory

    • James J. Buckley
    Pages 61-69

  7. Fuzzy Markov Chains

    • James J. Buckley
    Pages 71-83

  8. Fuzzy Decisions Under Risk

    • James J. Buckley
    Pages 85-93

  9. Continuous Fuzzy Random Variables

    • James J. Buckley
    Pages 95-108

  10. Fuzzy Inventory Control

    • James J. Buckley
    Pages 109-113

  11. Joint Fuzzy Probability Distributions

    • James J. Buckley
    Pages 115-123

  12. Applications of Joint Distributions

    • James J. Buckley
    Pages 125-132

  13. Functions of a Fuzzy Random Variable

    • James J. Buckley
    Pages 133-137

  14. Functions of Fuzzy Random Variables

    • James J. Buckley
    Pages 139-144

  15. Law of Large Numbers

    • James J. Buckley
    Pages 145-146

  16. Sums of Fuzzy Random Variables

    • James J. Buckley
    Pages 147-150

  17. Conclusions and Future Research

    • James J. Buckley
    Pages 151-155

  18. Back Matter

    Pages 157-166
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Keywords

About this book

In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability calculations we apply constrained fuzzy arithmetic because probabilities must add to one. Fuzzy random variables have fuzzy distributions. A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance. Applications are to queuing theory, Markov chains, inventory control, decision theory and reliability theory.

Authors and Affiliations

  • Mathematics Department, University of Alabama at Birmingham, Birmingham, USA

    James J. Buckley

Bibliographic Information

  • Book Title: Fuzzy Probabilities

  • Book Subtitle: New Approach and Applications

  • Authors: James J. Buckley

  • Series Title: Studies in Fuzziness and Soft Computing

  • DOI: https://doi.org/10.1007/978-3-642-86786-6

  • Publisher: Physica Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2003

  • Softcover ISBN: 978-3-642-86788-0Published: 01 June 2012

  • eBook ISBN: 978-3-642-86786-6Published: 06 December 2012

  • Series ISSN: 1434-9922

  • Series E-ISSN: 1860-0808

  • Edition Number: 1

  • Number of Pages: XII, 165

  • Topics: Artificial Intelligence

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