4 research outputs found
Fuzzy Sets, Fuzzy Logic and Their Applications
The present book contains 20 articles collected from amongst the 53 total submitted manuscripts for the Special Issue “Fuzzy Sets, Fuzzy Loigic and Their Applications” of the MDPI journal Mathematics. The articles, which appear in the book in the series in which they were accepted, published in Volumes 7 (2019) and 8 (2020) of the journal, cover a wide range of topics connected to the theory and applications of fuzzy systems and their extensions and generalizations. This range includes, among others, management of the uncertainty in a fuzzy environment; fuzzy assessment methods of human-machine performance; fuzzy graphs; fuzzy topological and convergence spaces; bipolar fuzzy relations; type-2 fuzzy; and intuitionistic, interval-valued, complex, picture, and Pythagorean fuzzy sets, soft sets and algebras, etc. The applications presented are oriented to finance, fuzzy analytic hierarchy, green supply chain industries, smart health practice, and hotel selection. This wide range of topics makes the book interesting for all those working in the wider area of Fuzzy sets and systems and of fuzzy logic and for those who have the proper mathematical background who wish to become familiar with recent advances in fuzzy mathematics, which has entered to almost all sectors of human life and activity
A modular genetic programming system
Genetic Programming (GP) is an evolutionary algorithm for the automatic
discovery of symbolic expressions, e.g. computer programs or mathematical
formulae, that encode solutions to a user-defined task. Recent advances in GP
systems and computer performance made it possible to successfully apply this
algorithm to real-world applications.
This work offers three main contributions to the state-of-the art in GP
systems:
(I) The documentation of RGP, a state-of-the art GP software implemented as an
extension package to the popular R environment for statistical computation and
graphics. GP and RPG are introduced both formally and with a series of tutorial
examples. As R itself, RGP is available under an open source license.
(II) A comprehensive empirical analysis of modern GP heuristics based on the
methodology of Sequential Parameter Optimization. The effects and interactions
of the most important GP algorithm parameters are analyzed and recommendations
for good parameter settings are given.
(III) Two extensive case studies based on real-world industrial applications.
The first application involves process control models in steel production,
while the second is about meta-model-based optimization of cyclone dust
separators. A comparison with traditional and modern regression methods
reveals that GP offers equal or superior performance in both applications,
with the additional benefit of understandable and easy to deploy models.
Main motivation of this work is the advancement of GP in real-world application
areas. The focus lies on a subset of application areas that are known to be
practical for GP, first of all symbolic regression and classification. It has
been written with practitioners from academia and industry in mind
General Adaptive Neighborhood-Based Pretopological Image Filtering
International audienceThis paper introduces pretopological image filtering in the context of the General Adaptive Neighborhood Image Processing (GANIP) approach. Pretopological filters act on gray level image while satisfying some topological properties. The GANIP approach enables to get an image representation and mathematical structure for adaptive image processing and analysis. Then, the combination of pretopology and GANIP leads to efficient image operators. They enable to process images while preserving region structures without damaging image transitions. More precisely, GAN-based pretopological filters and GAN-based viscous pretopological filters are proposed in this paper. The viscous notion enables to adjust the filtering activity to the image gray levels. These adaptive filters are evaluated through several experiments highlighting their efficiency with respect to the classical operators. They are practically applied in both the biomedical and material application areas for image restoration, image background subtraction and image enhancement