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Radon-Nikodym derivatives and conditioning in fuzzy measure theory.

Domenico Candeloro, Sabrina Pucci (1987)

Stochastica

In the last twenty years many papers have appeared dealing with fuzzy theory. In particular, fuzzy integration theory had its origin in the well-known Thesis of Sugeno [7]. More recently, some authors faced this topic by means of some binary operations (see for instance [3], [8] and references): a fuzzy measure must be additive with respect to one of them, an the integral is to define in a way, which is very similar to the construction of the Lebesgue integral. On the contrary, we are interested...

Relational Formal Characterization of Rough Sets

Adam Grabowski (2013)

Formalized Mathematics

The notion of a rough set, developed by Pawlak [10], is an important tool to describe situation of incomplete or partially unknown information. In this article, which is essentially the continuation of [6], we try to give the characterization of approximation operators in terms of ordinary properties of underlying relations (some of them, as serial and mediate relations, were not available in the Mizar Mathematical Library). Here we drop the classical equivalence- and tolerance-based models of rough...

Relative sets and rough sets

Amin Mousavi, Parviz Jabedar-Maralani (2001)

International Journal of Applied Mathematics and Computer Science

In this paper, by defining a pair of classical sets as a relative set, an extension of the classical set algebra which is a counterpart of Belnap's four-valued logic is achieved. Every relative set partitions all objects into four distinct regions corresponding to four truth-values of Belnap's logic. Like truth-values of Belnap's logic, relative sets have two orderings; one is an order of inclusion and the other is an order of knowledge or information. By defining a rough set as a pair of definable...

Relevance and redundancy in fuzzy classification systems.

Ana Del Amo, Daniel Gómez, Javier Montero, Gregory S. Biging (2001)

Mathware and Soft Computing

Fuzzy classification systems is defined in this paper as an aggregative model, in such a way that Ruspini classical definition of fuzzy partition appears as a particular case. Once a basic recursive model has been accepted, we then propose to analyze relevance and redundancy in order to allow the possibility of learning from previous experiences. All these concepts are applied to a real picture, showing that our approach allows to check quality of such a classification system.

Representation and construction of homogeneous and quasi-homogeneous n -ary aggregation functions

Yong Su, Radko Mesiar (2021)

Kybernetika

Homogeneity, as one type of invariantness, means that an aggregation function is invariant with respect to multiplication by a constant, and quasi-homogeneity, as a relaxed version, reflects the original output as well as the constant. In this paper, we characterize all homogeneous/quasi-homogeneous n -ary aggregation functions and present several methods to generate new homogeneous/quasi-homogeneous n -ary aggregation functions by aggregation of given ones.

Risk aversion, prudence and mixed optimal saving models

Irina Georgescu (2014)

Kybernetika

The paper studies risk aversion and prudence of an agent in the face of a risk situation with two parameters, one described by a fuzzy number, the other described by a fuzzy variable. The first contribution of the paper is the characterization of risk aversion and prudence in mixed models by conditions on the concavity and the convexity of the agent's utility function and its partial derivatives. The second contribution is the building of mixed models of optimal saving and their connection with...

Rough relation properties

Maria Nicoletti, Joaquim Uchoa, Margarete Baptistini (2001)

International Journal of Applied Mathematics and Computer Science

Rough Set Theory (RST) is a mathematical formalism for representing uncertainty that can be considered an extension of the classical set theory. It has been used in many different research areas, including those related to inductive machine learning and reduction of knowledge in knowledge-based systems. One important concept related to RST is that of a rough relation. This paper rewrites some properties of rough relations found in the literature, proving their validity.

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