Data-Driven Modelling with Fuzzy Sets: Embracing Uncertainty (Intelligent Data-Driven Systems and Artificial Intelligence)
Data-Driven Modelling with Fuzzy Sets : Embracing Uncertainty
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Data-Driven Modelling with Fuzzy Sets: Embracing Uncertainty (Intelligent Data-Driven Systems and Artificial Intelligence)
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This title will be released on May 22, 2026. Pre-order now. Express Delivery available with Amazon Prime.
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Data-Driven Modelling with Fuzzy Sets: Embracing Uncertainty (Intelligent Data-Driven Systems and Artificial Intelligence)
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Zadeh introduced in 1965 the theory of fuzzy sets, in which truth values are modelled by numbers in the unit interval [0, 1], for tackling mathematically the frequently appearing in everyday life partial truths.In a second stage, when membership functions were reinterpreted as possibility distributions, fuzzy sets were extensively used to embrace uncertainty modelling.Uncertainty is defined as the shortage of precise knowledge or complete information and possibility theory is devoted to the handling of incomplete information.Zadeh articulated the relationship between possibility and probability, noticing that what is probable must preliminarily be possible.Following the Zadeh’s fuzzy set, various generalizations (intuitionistic, neutrosophic, rough, soft sets, etc.) have been introduced enabling a more effective management of all types of the existing in real world uncertainty.This book presents recent theoretical advances and applications of fuzzy sets and their extensions to Science,
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