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

✍ Scribed by József Dombi, Tamás Jónás

Publisher
Springer International Publishing;Springer
Year
2021
Tongue
English
Leaves
201
Series
Studies in Computational Intelligence 814
Edition
1st ed.
Category
Library
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✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-xvii
Belief, Probability and Plausibility (József Dombi, Tamás Jónás)....Pages 1-26
(\lambda )-Additive and (\nu )-Additive Measures (József Dombi, Tamás Jónás)....Pages 27-83
The Pliant Probability Distribution Family (József Dombi, Tamás Jónás)....Pages 85-134
A Fuzzy Arithmetic-Based Time Series Model (József Dombi, Tamás Jónás)....Pages 135-165
Likert Scale-Based Evaluations with Flexible Fuzzy Numbers (József Dombi, Tamás Jónás)....Pages 167-187

✦ Subjects

Engineering; Computational Intelligence

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