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

• Autore: Dombi József
• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
• Edizione: 1st ed. 2021.
• Descrizione fisica: 1 online resource (201 pages)
• Disciplina: 519.2
• Soggetto topico: Engineering—Data processing; Computational intelligence; Data Engineering; Computational Intelligence
• Persona (resp. second.): JónásTamás
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications
• ISBN: 3-030-51949-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910484105403321
• Lo trovi qui: Univ. Federico II
• Serie: Studies in Computational Intelligence, . 1860-949X ; ; 814