Search results for "Fuzzy"

A Formal Skeleton of Commonsense Reasoning

2022

After referring several times to Commonsense or Ordinary Reasoning, let’s devote a few pages to present a (minimal) mathematical model of it that can be seen as the ‘Skeleton’ of Reasoning, since it is defined by a set of few, simple laws appearing in the models of particular and specialized modes of reasoning like, for instance: Boolean Algebras for the reasoning with precise concepts; Orto-modular lattices for the reasoning with the concepts of Quantum Physics; and also in the so called Algebras of Fuzzy Sets for the reasoning with imprecise concepts, and among them De Morgan-Kleene algebras. All these models have interesting applications.

Fuzzy Logic, Vagueness and Uncertainty

2009

Automatic detection of cardiac contours on MR Images using fuzzy logic and dynamic programming

1997

International audience; Abstract: This paper deals with the use of fuzzy logic and dynamic programming in the detection of cardiac contours in MR Images. The definition of two parameters for each pixel allows the construction of the fuzzy set of the cardiac contour points. The first parameter takes into account the grey level, and the second the presence of an edge. A corresponding fuzzy matrix is derived from the initial image. Finally, a dynamic programming with graph searching is performed on this fuzzy matrix. The method has been tested on several MR images and the results of the contouring were validated by an expert in the domain. This preliminary work clearly demonstrates the interes…

On the evaluation of image complexity: a fuzzy approach

2005

Fuzzy Set Theory as a methodological bridge between hard science and humanities

2014

In this paper, we will investigate the possible role of fuzzy set theory (FST), and more generally the ensemble of technologies and theoretical approaches known as soft computing, as a method- ological bridge between hard sciences and humanities. We will try, building on previous works, to investigate the “family links” between these disciplines and show how FST may be of help in promoting a connection between the “two cultures”. We will discuss Carnap and his paradox of explication, the dilemma between imagination and rigor according to Bateson, the problem of interdisciplinarity, and the consequences of precision and exactness.

Representation of knowledge using Fuzzy set theory

1989

Fuzzy methods for analysing fuzzy production environment

1998

Abstract Very recently, in production management research literature, the necessity to extend production systems analysis techniques, such as queue theory, Mean Value Analysis (MVA) and discrete simulation, to Fuzzy Production Environments, i.e. to those production situations in which data are vague, has emerged. Fuzzy set theory is a powerful tool to model vagueness and, therefore, fuzzy mathematics can be used to extend classical production system analysis techniques. This paper proposes a methodology based on fuzzy relation algebra to extend classical MVA and discrete event simulation.

A fuzzy framework to explain musical tuning in practice

2013

A theoretical tuning system is a set of pitches that can be used to play music. It is a fact that the human ear perceives notes with very close frequencies as if they were the same note. Therefore, in our approach a musical note and its pitch sensation are modeled as L-R fuzzy numbers with a modal interval and a bounded support. We pay particular attention to the 12-tone equal temperament (12-TET) for being the most widely used tuning system and we define the fuzzy 12-TET composed of 12 fuzzy notes. A similarity relation between a fuzzy note and a theoretical note can be defined, and subsequently a similarity class associated to each one of the fuzzy notes in the fuzzy 12-TET arises. Finall…

An integrated fuzzy cells-classifier

2007

This paper introduces a genetic algorithm able to combine different classifiers based on different distance functions. The use of a genetic algorithm is motivated by the fact that the combination phase is based on the optimization of a vote strategy. The method has been applied to the classification of four types of biological cells, results show an improvement of the recognition rate using the genetic algorithm combination strategy compared with the recognition rate of each single classifier.

A genetic integrated fuzzy classifier

2005

This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.