Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications [electronic resource] / by József Dombi, Tamás Jónás.

За: Інтелектуальна відповідальність: Вид матеріалу: Текст Серія: Studies in Computational Intelligence ; 814Публікація: Cham : Springer International Publishing : Imprint: Springer, 2021Видання: 1st ed. 2021Опис: XVII, 187 p. 67 illus. online resourceТип вмісту:
  • text
Тип засобу:
  • computer
Тип носія:
  • online resource
ISBN:
  • 9783030519490
Тематика(и): Додаткові фізичні формати: Printed edition:: Немає назви; Printed edition:: Немає назви; Printed edition:: Немає назвиДесяткова класифікація Дьюї:
  • 620.00285 23
Класифікація Бібліотеки Конгресу:
  • TA345-345.5
Електронне місцезнаходження та доступ:
Вміст:
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.
У: Springer Nature eBookЗведення: 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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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.

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