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Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications: Studies in Computational Intelligence, cartea 814

Autor József Dombi, Tamás Jónás
en Limba Engleză Hardback – 12 aug 2020
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.   

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Specificații

ISBN-13: 9783030519483
ISBN-10: 3030519481
Ilustrații: XVII, 187 p. 67 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.47 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Belief, probability and plausibility.- λ-additive and ν-additive measures.- The pliant probability distribution family.- A fuzzy arithmetic-based time series model.- Likert scale-based evaluations with flexible fuzzy numbers.- Bibliography.

Textul de pe ultima copertă

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.

Caracteristici

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