Search results for "Fuzzy Logic."

showing 10 items of 449 documents

Paradigm of tunable clustering using Binarization of Consensus Partition Matrices (Bi-CoPaM) for gene discovery

2013

Copyright @ 2013 Abu-Jamous et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Clustering analysis has a growing role in the study of co-expressed genes for gene discovery. Conventional binary and fuzzy clustering do not embrace the biological reality that some genes may be irrelevant for a problem and not be assigned to a cluster, while other genes may participate in several biological functions and should simultaneously belong to multiple clusters. Also, these algorithms cannot generate tight cluster…

Fuzzy clusteringMicroarraysSingle-linkage clusteringGenes FungalGene Expressionlcsh:MedicineBiologyFuzzy logicSet (abstract data type)Molecular GeneticsEngineeringGenome Analysis ToolsYeastsConsensus clusteringMolecular Cell BiologyDatabases GeneticCluster (physics)GeneticsCluster AnalysisBinarization of Consensus Partition Matrices (Bi-CoPaM)Cluster analysislcsh:ScienceGene clusteringBiologyOligonucleotide Array Sequence AnalysisGeneticsMultidisciplinarybusiness.industryCell Cycleta111lcsh:RComputational BiologyPattern recognitionGenomicsgene discoveryPartition (database)tunable binarization techniquesComputingMethodologies_PATTERNRECOGNITIONGenesCell cyclesSignal Processinglcsh:QArtificial intelligencebusinessGenomic Signal ProcessingAlgorithmsResearch Articleclustering
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Fuzzy modeling of solar irradiance on inclined surfaces

2003

A model of solar irradiance on arbitrarily oriented inclined surfaces is proposed, based on fuzzy logic procedures. The behavior of the proposed model is similar to that of other models of increased performance such as the models of Perez or Gueymard, though it requires only a very limited number of classes and adjustable parameters. The use of fuzzy clustering optimizes the number and definition of the sky categories. The model considers overlapping clusters and allows an improved description of the sky situations close to the transition zone between contiguous categories.

Fuzzy clusteringRenewable Energy Sustainability and the EnvironmentComputer scienceSkymedia_common.quotation_subjectGeneral Materials ScienceSolar irradianceAlgorithmFuzzy logicRemote sensingmedia_commonSolar Energy
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Gravitational weighted fuzzy c-means with application on multispectral image segmentation

2014

This paper presents a novel clustering approach based on the classic Fuzzy c-means algorithm. The approach is inspired from the concept of interaction between objects in physics. Each data point is regarded as a particle. A specific weight is associated with each data particle depending on its interaction with other particles. This interaction is induced by attraction forces between pairs of particles and the escape velocity from other particles. Classification experiments using two data sets from UCI repository demonstrate the outperformance of the proposed approach over other clustering algorithms. In addition, results demonstrate the effectiveness of the proposed scheme for segmentation …

Fuzzy clusteringSegmentation-based object categorizationbusiness.industryCorrelation clusteringScale-space segmentationPattern recognitionSegmentationImage segmentationArtificial intelligenceCluster analysisbusinessFuzzy logicMathematics2014 4th International Conference on Image Processing Theory, Tools and Applications (IPTA)
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Accurate detection and characterization of corner points using circular statistics and fuzzy clustering

1998

Accurate detection and characterization of corner points in grey level images is considered as a pattern recognition problem. The method considers circular statistic tests to detect 2D features. A fuzzy clustering algorithm is applied to the edge orientations near the prospective corners to detect and classify them. The method is based on formulating hypotheses about the distribution of these orientations around an edge, corner or other 2-D feature. The method may provide accurate estimates of the direction of the edges that converge in a corner, along with their confidence intervals. Experimental results show the method to be robust enough against noise and contrast changes. Fuzzy membersh…

Fuzzy clusteringbusiness.industryComputer scienceContrast (statistics)Pattern recognitionFuzzy logicFeature (computer vision)Pattern recognition (psychology)Computer visionNoise (video)Enhanced Data Rates for GSM EvolutionArtificial intelligencebusinessStatistic
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Fuzzy Discrete Event Simulation for Fuzzy Production Systems Analysis

1998

Abstract Fuzzy production systems are characterised by vagueness in data and requirements that very often cannot be reduced to stochastic models. Therefore, such production systems cannot be analysed by using classical techniques such as Queue Theory or Discrete Simulation Analysis. On the other hand the great diffusion of Fuzzy Production environments in small and medium enterprises claims for the development of new analysis tools. This paper proposes a new approach to Discrete Event Simulation able to treat with fuzzy variables. A new methodology has been proposed to process fuzzy information within discrete event simulation and a prototype of a Fuzzy Discrete Event Simulator has been dev…

Fuzzy electronicsFuzzy transportationNeuro-fuzzyStochastic modellingComputer scienceFuzzy set operationsFuzzy associative matrixControl engineeringFuzzy control systemDiscrete event simulationFuzzy logicDefuzzificationIFAC Proceedings Volumes
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Decision Suport System for Manufacturing Processes Reengineering based upon Fuzzy Logic Techniques

2012

Abstract This work presents a method for taking the decision of reengineering a production system, based upon fuzzy techniques. The main advantage of this method is, after authors' opinion, is the ease of its implementation together with the reduced time for gathering data and processing it. Multi-variable decision systems are usually based upon complicated mathematical methods and involved a large amount of data to be processed. The fuzzy approach presented here is based only on five input variables and one output variable. The data for the model are gathered by simple queries and quizzes. Human perception, the main point of fuzzy logic, is widely used here for gathering input data for the…

Fuzzy electronicsVariable (computer science)Point (typography)Computer scienceSimple (abstract algebra)Fuzzy set operationsGeneral MedicineBusiness process reengineeringData miningcomputer.software_genreFuzzy logicDecision modelcomputerIFAC Proceedings Volumes
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Automatic Monitoring System for the Evolution of the Hemangiomas

2019

In this paper we describe an automatic monitoring system for the evolution of infantile hemangiomas using a fuzzy logic system based on two parameters: area and redness. To follow the evolution, we have used for each subject pairs of images at different moments of time. The starting points of the algorithm are the rectangular regions of interest (ROI), manually selected for each of the two images, and automatically segmented using Otsu’s method in combination with different preprocessing methods. Using the results of segmentation, we could compute the evolution of the area and the evolution of the redness of hemangioma. These two parameters were used as input for the fuzzy logic system, obt…

Fuzzy logic systemComputer sciencebusiness.industryMonitoring systemPattern recognitionmedicine.diseaseFuzzy logicOtsu's methodHemangiomasymbols.namesakemedicinesymbolsPreprocessorSegmentationArtificial intelligencebusiness2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE)
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Asymptotic comparison of the implicative fragments of certain fuzzy logics

2022

An asymptotic similarity of some fragments of two fuzzy logics is proved. We focus on two 3-valued fuzzy logics: the Gödel-Dummett one and the Łukasiewicz one and we consider their purely implicative fragments of two variables. This paper shows the existence of the densities of truth of these logics and determines their values. For this purpose we build the appropriate Tarski-Lindenbaum algebra and use extensively generating functions. Our method can be generalized to n-valued logics, n > 3, but all computations will be extremely complicated.

Fuzzy logicAlgebraFuzzy systems
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Fuzzy fixed points of generalized F2-geraghty type fuzzy mappings and complementary results

2016

The aim of this paper is to introduce generalized F2-Geraghty type fuzzy mappings on a metric space for establishing the existence of fuzzy fixed points of such mappings. As an application of our result, we obtain the existence of common fuzzy fixed point for a generalized F2-Geraghty type fuzzy hybrid pair. These results unify, generalize and complement various known comparable results in the literature. An example and an application to theoretical computer science are presented to support the theory proved herein. Also, to suggest further research on fuzzy mappings, a Feng–Liu type theorem is proved.

Fuzzy mappingSorting algorithmFuzzy classificationMathematics::General MathematicsFuzzy mappingFuzzy fixed pointlcsh:Analysis02 engineering and technologyType (model theory)01 natural sciencesFuzzy logicfuzzy fixed point fuzzy mapping sorting algorithmSettore MAT/05 - Analisi Matematica0202 electrical engineering electronic engineering information engineeringFuzzy number0101 mathematicsMathematicsDiscrete mathematicsSorting algorithmApplied Mathematicslcsh:QA299.6-433010101 applied mathematicsFuzzy mathematicsFuzzy set operations020201 artificial intelligence & image processingAnalysis
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Optimization Under Fuzzy Max-t-Norm Relation Constraints

2019

Fuzzy relation equations and inequalities play an important role in many tools of fuzzy modelling and have been extensively studied. In many practical applications they are used as constraints in optimization. Algorithms for specific objective functions have been proposed by many authors. In this paper we introduce a method to convert a system of fuzzy relation constraints with max-t-norm composition to a linear constraint system by adding integer variables. A numerical example is provided to illustrate the proposed method.

Fuzzy modellingConstraint (information theory)Mathematical optimizationRelation (database)Mathematics::Metric GeometryT-normComposition (combinatorics)Fuzzy logicMathematicsInteger (computer science)
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