Titlebook: Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools; József Dombi,Orsolya Csiszár Book 2021 The Editor(s) (

未成熟

https://doi.org/10.1007/978-1-4757-5380-6fferentiability; a property that would be useful for learning systems. In this chapter, we introduce the so-called squashing functions; a differentiable parametrized family of functions that can not only be used for approximating piecewise linear membership functions but also Łukasiewicz-type logica

朋党派系

https://doi.org/10.1007/978-3-030-72280-7Computational Intelligence; Neural Networks; Explainable Neural Networks; Fuzzy Logic; Multi-criteria De

强有力

Connectives: Conjunctions, Disjunctions and Negationsonable to study fuzzy logical systems, where these laws hold. In this chapter, we give a full description of consistent conjunction, disjunction, and negation triples in such systems. We also introduce additional negation operators that naturally define thresholds for better modeling of human thinki

不爱防注射

违法事实

thwart

的阐明

Aggregative Operatorscus on nilpotent logical systems and describe aggregative operators in such systems ranging from symmetric ones (that treat all the inputs equally) to weighted ones, where some inputs are given more weight than others. As a starting point, instead of associativity, we focus on the necessary and suff

嘲弄

infinite

Squashing Functionsfferentiability; a property that would be useful for learning systems. In this chapter, we introduce the so-called squashing functions; a differentiable parametrized family of functions that can not only be used for approximating piecewise linear membership functions but also Łukasiewicz-type logica

extinct