Search results for " Computer Science"

showing 10 items of 3983 documents

The Power of the “Pursuit” Learning Paradigm in the Partitioning of Data

2019

Traditional Learning Automata (LA) work with the understanding that the actions are chosen purely based on the “state” in which the machine is. This modus operandus completely ignores any estimation of the Random Environment’s (RE’s) (specified as \(\mathbb {E}\)) reward/penalty probabilities. To take these into consideration, Estimator/Pursuit LA utilize “cheap” estimates of the Environment’s reward probabilities to make them converge by an order of magnitude faster. This concept is quite simply the following: Inexpensive estimates of the reward probabilities can be used to rank the actions. Thereafter, when the action probability vector has to be updated, it is done not on the basis of th…

Mathematical optimizationTheoretical computer scienceLearning automataBasis (linear algebra)Computer scienceRank (computer programming)Object PartitioningPartitioning-based learningEstimatorLearning Automata02 engineering and technologyProbability vectorField (computer science)AutomatonRanking0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing[INFO]Computer Science [cs]Object Migration Automaton
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Optimal Paths on Urban Networks Using Travelling Times Prevision

2012

We deal with an algorithm that, once origin and destination are fixed, individuates the route that permits to reach the destination in the shortest time, respecting an assigned maximal travel time, and with risks measure below a given threshold. A fluid dynamic model for road networks, according to initial car densities on roads and traffic coefficients at junctions, forecasts the future traffic evolution, giving dynamical weights to a constrained 𝐾 shortest path algorithm. Simulations are performed on a case study to test the efficiency of the proposed procedure.

Mathematical optimizationTraffic congestion reconstruction with Kerner's three-phase theoryArticle SubjectComputer scienceFluid dynamic model; K shortest path algorithm; Travelling times previsionGeneral EngineeringTraffic simulationK shortest path algorithmMeasure (mathematics)lcsh:QA75.5-76.95Computer Science ApplicationsTraffic congestionFluid dynamic modelModeling and SimulationShortest path problemComputer Science::Networking and Internet Architecturelcsh:Electronic computers. Computer scienceTravelling times previsionDijkstra's algorithmConstrained Shortest Path FirstSimulationTraffic waveModelling and Simulation in Engineering
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The Rural Postman Problem on mixed graphs with turn penalties

2002

In this paper we deal with a problem which generalizes the Rural Postman Problem defined on a mixed graph (MRPP). The generalization consists of associating a non-negative penalty to every turn as well as considering the existence of forbidden turns. This new problem fits real-world situations more closely than other simpler problems. A solution tour must traverse all the requiring service arcs and edges of the graph while not making forbidden turns. Its total cost will be the sum of the costs of the traversed arcs and edges together with the penalties associated with the turns done. The Mixed Rural Postman Problem with Turn Penalties (MRPPTP) consists of finding such a tour with a total mi…

Mathematical optimizationTraverseGeneral Computer SciencePolynomial transformationTotal costMixed graphManagement Science and Operations ResearchTravelling salesman problemModeling and SimulationComputer Science::Data Structures and AlgorithmsHeuristicsArc routingMetaheuristicMathematicsComputers & Operations Research
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Using penalties instead of rewards: Solving OCST problems with guided local search

2012

Abstract This paper considers the optimal communication spanning tree (OCST) problem. Previous work analyzed features of high-quality solutions and found that edges in optimal solutions have low weight and point towards the center of a tree. Consequently, integrating this problem-specific knowledge into a metaheuristic increases its performance for the OCST problem. In this paper, we present a guided local search (GLS) approach which dynamically changes the objective function to guide the search process into promising areas. In contrast to traditional approaches which reward promising solution features by favoring edges with low weights pointing towards the tree’s center, GLS penalizes low-…

Mathematical optimizationTree (data structure)Spanning treeGeneral Computer ScienceOrientation (computer vision)Computer scienceGeneral MathematicsCombinatorial optimizationContrast (statistics)Point (geometry)Guided Local SearchMetaheuristicSwarm and Evolutionary Computation
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Decision-aid for discrete multiple criteria decision making problems with imprecise data

1999

Abstract We describe ways of aiding decision making with a discrete set of alternatives. In many decision situations, it is not possible to obtain explicit preference information from the decision makers. Instead, useful decision-aid can be provided to the decision makers by describing what kind of weighting of the criteria result in certain choices of the alternatives. The suggested treatment is based on the basic ideas of the ELECTRE III method. The modelling of the preferences by pseudo-criteria is especially helpful in case the data, that is, the criterion values are imprecise. Unlike ELECTRE III, no ranking of the alternatives is produced. Based on a minimum-procedure in the exploitati…

Mathematical optimizationWeighted sum modelInformation Systems and ManagementGeneral Computer ScienceWeighted product modelEvidential reasoning approachDecision ruleManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringModeling and SimulationInfluence diagramELECTREOptimal decisionMathematicsDecision analysisEuropean Journal of Operational Research
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Solving the pentahedron problem

2015

Nowadays, all geometric modelers provide some tools for specifying geometric constraints. The 3D pentahedron problem is an example of a 3D Geometric Constraint Solving Problem (GCSP), composed of six vertices, nine edges, five faces (two triangles and three quadrilaterals), and defined by the lengths of its edges and the planarity of its quadrilateral faces. This problem seems to be the simplest non-trivial problem, as the methods used to solve the Stewart platform or octahedron problem fail to solve it. The naive algebraic formulation of the pentahedron yields an under-constrained system of twelve equations in eighteen unknowns. Even if the use of placement rules transforms the pentahedron…

Mathematical optimization[ INFO ] Computer Science [cs]Interval (mathematics)[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]Industrial and Manufacturing EngineeringDesargues’ theoremPolyhedronAl-Kashi theorem[INFO]Computer Science [cs]Algebraic numberFinite setMathematicsGeometric constraint solving problemsQuadrilateralGeometric modeling with constraintsSolution set[ MATH.MATH-NA ] Mathematics [math]/Numerical Analysis [math.NA]SolverComputer Graphics and Computer-Aided DesignPentahedronPentahedronComputer Science ApplicationsAlgebraInterval solver[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG][MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
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Using the witness method to detect rigid subsystems of geometric constraints in CAD

2010

International audience; This paper deals with the resolution of geometric constraint systems encountered in CAD-CAM. The main results are that the witness method can be used to detect that a constraint system is over-constrained and that the computation of the maximal rigid subsystems of a system leads to a powerful decomposition method. In a first step, we recall the theoretical framework of the witness method in geometric constraint solving and extend this method to generate a witness. We show then that it can be used to incrementally detect over-constrainedness. We give an algorithm to efficiently identify all maximal rigid parts of a geometric constraint system. We introduce the algorit…

Mathematical optimization[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulationrigidity theorygeometric constraints solvingComputation020207 software engineeringCADJacobian matrix02 engineering and technologyW-decompositionwitness configuration16. Peace & justiceWitness[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulationsymbols.namesakeJacobian matrix and determinant0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processingRigidity theoryAlgorithmAlgorithmsMathematics
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Analysis of human skin hyper-spectral images by non-negative matrix factorization

2011

International audience; This article presents the use of Non-negative Matrix Factorization, a blind source separation algorithm, for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The evaluated spectra come from a Hyper-Spectral Image, which is the result of the processing of a Multi-Spectral Image by a neural network-based algorithm. The implemented source separation algorithm is based on a multiplicative coeffi cient upload. The goal is to represent a given spectrum as the weighted sum of two spectral components. The resulting weighted coefficients are used to quantify melanin and hemoglobin content in the given spectra. Results present a …

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingAbsorption spectroscopy[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMelasmaComputer sciencePhysics::Medical PhysicsPopulation[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesNon-negative Matrix FactorizationSpectral line030218 nuclear medicine & medical imagingNon-negative matrix factorizationMatrix decomposition010309 opticsBlind source separation algorithms03 medical and health sciences0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciencesSource separationmedicineMulti/Hyper-Spectral imagingeducation[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingeducation.field_of_studyArtificial neural networkbusiness.industrySpectrum (functional analysis)Pattern recognitionmedicine.diseaseArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processinghuman skin absorbance spectrum
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Subsignal-based denoising from piecewise linear or constant signal

2011

15 pages; International audience; n the present work, a novel signal denoising technique for piecewise constant or linear signals is presented termed as "signal split." The proposed method separates the sharp edges or transitions from the noise elements by splitting the signal into different parts. Unlike many noise removal techniques, the method works only in the nonorthogonal domain. The new method utilizes Stein unbiased risk estimate (SURE) to split the signal, Lipschitz exponents to identify noise elements, and a polynomial fitting approach for the sub signal reconstruction. At the final stage, merging of all parts yield in the fully denoised signal at a very low computational cost. St…

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceStochastic resonanceNoise reduction[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciencesMultiplicative noisePiecewise linear function010104 statistics & probabilitySpeckle patternsymbols.namesakeSignal-to-noise ratioWavelet[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineering0101 mathematicsSignal transfer functionShrinkageSignal reconstructionNoise (signal processing)General EngineeringNonlinear opticsWavelet transform020206 networking & telecommunicationsTotal variation denoisingAtomic and Molecular Physics and OpticsAdditive white Gaussian noiseGaussian noisePiecewisesymbolsStep detectionAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Non Linear Image Restoration in Spatial Domain

2011

International audience; In the present work, a novel image restoration method from noisy data samples is presented. The restoration was per-formed by using some heuristic approach utilizing data samples and smoothness criteria in spatial domain. Unlike most existing techniques, this approach does not require prior modelling of either the image or noise statistics. The proposed method works in an interactive mode to find the best compromise between the data (mean square error) and the smoothing criteria. The method has been compared with the shrinkage approach, Wiener filter and Non Local Means algorithm as well. Experimental results showed that the proposed method gives better signal to noi…

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingNoise reductionWiener filter020206 networking & telecommunications02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingNon-local meansMultiplicative noisesymbols.namesakeMean Square ErrorSignal-to-noise ratio[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingGaussian noiseSignal SmoothnessRestoration0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmSmoothingImage restorationNonlinear FilteringMathematics
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