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Advances in the theory of probabilis...

Dombi, Jozsef.

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Advances in the theory of probabilistic and fuzzy data scientific methods with applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advances in the theory of probabilistic and fuzzy data scientific methods with applications/ by Jozsef Dombi, Tamas Jonas.
作者:	Dombi, Jozsef.
其他作者:	Jonas, Tamas.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xvii, 187 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Probabilities. -
電子資源:	https://doi.org/10.1007/978-3-030-51949-0
ISBN:	9783030519490

Advances in the theory of probabilistic and fuzzy data scientific methods with applications
Dombi, Jozsef.

Advances in the theory of probabilistic and fuzzy data scientific methods with applications[electronic resource] /by Jozsef Dombi, Tamas Jonas. - Cham :Springer International Publishing :2021. - xvii, 187 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8141860-949X ;. - Studies in computational intelligence ;v.814..

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.

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.

ISBN: 9783030519490

Standard No.: 10.1007/978-3-030-51949-0doiSubjects--Topical Terms:

518889
Probabilities.

LC Class. No.: QA273 / .D65 2021

Dewey Class. No.: 519.2

Advances in the theory of probabilistic and fuzzy data scientific methods with applications
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