Search results for "Computer Science Application"

showing 10 items of 3998 documents

How to simulate normal data sets with the desired correlation structure

2010

The Cholesky decomposition is a widely used method to draw samples from multivariate normal distribution with non-singular covariance matrices. In this work we introduce a simple method by using singular value decomposition (SVD) to simulate multivariate normal data even if the covariance matrix is singular, which is often the case in chemometric problems. The covariance matrix can be specified by the user or can be generated by specifying a subset of the eigenvalues. The latter can be an advantage for simulating data sets with a particular latent structure. This can be useful for testing the performance of chemometric methods with data sets matching the theoretical conditions for their app…

Mathematical optimizationCovariance functionCovariance matrixProcess Chemistry and TechnologyMathematicsofComputing_NUMERICALANALYSISMultivariate normal distributionCovarianceComputer Science ApplicationsAnalytical ChemistryEstimation of covariance matricesScatter matrixMatrix normal distributionCMA-ESAlgorithmComputer Science::DatabasesSpectroscopySoftwareMathematicsChemometrics and Intelligent Laboratory Systems
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STUDY OF VOLUME VARIATION OF IMPLICIT OBJECTS

2006

We propose studying the variations of volume of implicit objects during an animation according to several points of view: choice of the function of density, variations of parameters such as the iso-value and the radius of influence for a given function, variations of the parameters inherent in a particular function. Modification of parameters of the function of density must be carried out with care. There are no rules concerning these variations. To avoid the non-monotonous variations, it is necessary to choose a function of density beforehand and study the intervals of variation of its parameters. A new discretization makes it possible to locate these variations for a later use in a proce…

Mathematical optimizationDiscretizationComputer scienceVolume variationProcess (computing)Volume (computing)Function (mathematics)AnimationVariation (game tree)Computer Graphics and Computer-Aided DesignComputer Science ApplicationsRadius of influenceComputer Vision and Pattern RecognitionAlgorithmInternational Journal of Image and Graphics
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A multi-parametric evolution strategies algorithm for vehicle routing problems

2007

Vehicle routing problems are at the heart of most decision support systems for real-life distribution problems. In vehicle routing problem a set of routes must be determined at lowest total cost for a number of resources (i.e. fleet of vehicles) located at one or several points (e.g. depots, warehouses) in order to efficiently service a number of demand or supply points. In this paper an efficient evolution strategies algorithm is developed for both capacitated vehicle routing problem and for vehicle routing problem with time window constraints. The algorithm is based on a new multi-parametric mutation procedure that is applied within the 1 + 1 evolution strategies algorithm. Computational …

Mathematical optimizationDynamic Source RoutingSDG 16 - PeaceComputer scienceEqual-cost multi-path routingEvolution strategiesArtificial IntelligenceVehicle routing problemVehicle routing problemHeuristicsDestination-Sequenced Distance Vector routingTriangular routingStatic routingDistribution managementPolicy-based routingSDG 16 - Peace Justice and Strong InstitutionsGeneral EngineeringPath vector protocol/dk/atira/pure/sustainabledevelopmentgoals/peace_justice_and_strong_institutionsJustice and Strong InstitutionsComputer Science ApplicationsDistance-vector routing protocolLink-state routing protocolMultipath routingHeuristicsAlgorithmExpert systems with applications
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Statistical criteria for early-stopping of support vector machines

2007

This paper proposes the use of statistical criteria for early-stopping support vector machines, both for regression and classification problems. The method basically stops the minimization of the primal functional when moments of the error signal (up to fourth order) become stationary, rather than according to a tolerance threshold of primal convergence itself. This simple strategy induces lower computational efforts and no significant differences are observed in terms of performance and sparsity.

Mathematical optimizationEarly stoppingStructured support vector machinebusiness.industryCognitive NeuroscienceMachine learningcomputer.software_genreRegressionProbability vectorComputer Science ApplicationsSupport vector machineRelevance vector machineArtificial IntelligenceConvergence (routing)MinificationArtificial intelligencebusinesscomputerMathematicsNeurocomputing
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Modelling agricultural risk in a large scale positive mathematical programming model

2020

International audience; Mathematical programming has been extensively used to account for risk in farmers' decision making. The recent development of the positive mathematical programming (PMP) has renewed the need to incorporate risk in a more robust and flexible way. Most of the existing PMP-risk models have been tested at farm-type level and for a very limited sample of farms. This paper presents and tests a novel methodology for modelling risk at individual farm level in a large scale model, called individual farm model for common agricultural policy analysis (IFM-CAP). Results show a clear trade-off between including and excluding the risk specification. Albeit both alternatives provid…

Mathematical optimizationEconomics and EconometricsScale (ratio)Computer scienceComputationprogrammation mathématique positive020209 energyexpected utilitySample (statistics)highest posterior density02 engineering and technologypolitique agricole communerisk and uncertainty0202 electrical engineering electronic engineering information engineeringEuropean common agricultural policyExpected utility hypothesisagricultureEstimationrisque et incertitude2. Zero hungerbusiness.industry020208 electrical & electronic engineering[SHS.ECO]Humanities and Social Sciences/Economics and Finance16. Peace & justicemodèle de fermePMPComputer Science ApplicationsAgriculturebusinessCommon Agricultural PolicyScale modelpositive mathematical programmingInternational Journal of Computational Economics and Econometrics
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Multidisciplinary shape optimization in aerodynamics and electromagnetics using genetic algorithms

1999

SUMMARY A multiobjective multidisciplinary design optimization (MDO) of two-dimensional airfoil is presented. In this paper, an approximation for the Pareto set of optimal solutions is obtained by using a genetic algorithm (GA). The first objective function is the drag coefficient. As a constraint it is required that the lift coefficient is above a given value. The CFD analysis solver is based on the finite volume discretization of the inviscid Euler equations. The second objective function is equivalent to the integral of the transverse magnetic radar cross section (RCS) over a given sector. The computational electromagnetics (CEM) wave field analysis requires the solution of a two-dimensi…

Mathematical optimizationElectromagneticsHelmholtz equationFictitious domain methodApplied MathematicsMechanical EngineeringMultidisciplinary design optimizationComputational MechanicsSolverComputer Science ApplicationsEuler equationssymbols.namesakeMechanics of MaterialssymbolsComputational electromagneticsShape optimizationMathematicsInternational Journal for Numerical Methods in Fluids
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A survey on handling computationally expensive multiobjective optimization problems using surrogates: non-nature inspired methods

2015

Computationally expensive multiobjective optimization problems arise, e.g. in many engineering applications, where several conflicting objectives are to be optimized simultaneously while satisfying constraints. In many cases, the lack of explicit mathematical formulas of the objectives and constraints may necessitate conducting computationally expensive and time-consuming experiments and/or simulations. As another challenge, these problems may have either convex or nonconvex or even disconnected Pareto frontier consisting of Pareto optimal solutions. Because of the existence of many such solutions, typically, a decision maker is required to select the most preferred one. In order to deal wi…

Mathematical optimizationEngineeringControl and Optimizationbusiness.industryPareto principlePareto frontierDecision makerSampling techniqueComputer Graphics and Computer-Aided DesignMulti-objective optimizationComputer Science ApplicationsMultiobjective optimization problemPareto optimalConflicting objectivesBlack-box functionControl and Systems EngineeringMulticriteria Decision Making (MCDM)Computational costNature inspiredMetamodeling techniquebusinessEngineering design processSoftwareStructural and Multidisciplinary Optimization
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Applying the approximation method PAINT and the interactive method NIMBUS to the multiobjective optimization of operating a wastewater treatment plant

2014

Using an interactive multiobjective optimization method called NIMBUS and an approximation method called PAINT, preferable solutions to a five-objective problem of operating a wastewater treatment plant are found. The decision maker giving preference information is an expert in wastewater treatment plant design at the engineering company Pöyry Finland Ltd. The wastewater treatment problem is computationally expensive and requires running a simulator to evaluate the values of the objective functions. This often leads to problems with interactive methods as the decision maker may get frustrated while waiting for new solutions to be computed. Thus, a newly developed PAINT method is used to spe…

Mathematical optimizationEngineeringOR in natural resourcesControl and OptimizationSpeedupbusiness.industryApplied Mathematicsproductivity and competitivenessManagement Science and Operations ResearchsimulationDecision makerMulti-objective optimizationIndustrial and Manufacturing EngineeringComputer Science ApplicationsSet (abstract data type)Pareto optimalmultiple objective programmingSewage treatmentPlant designbusinessta218Integer (computer science)
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A contribution on the optimization strategies based on moving least squares approximation for sheet metal forming design

2012

Computer-aided procedures to design and optimize forming processes are, nowadays, crucial research topics since industrial interest in costs and times reduction is always increasing. Many researchers have faced this research challenge with various approaches. Response surface methods (RSM) are probably the most known approaches since they proved their effectiveness in the recent years. With a peculiar attention to sheet metal forming process design, RSM should offer the possibility to reduce the number of numerical simulations which in many cases means to reduce design times and complexity. Actually, the number of direct problems (FEM simulations) to be solved in order to reach good functio…

Mathematical optimizationEngineeringOptimization problembusiness.industryMechanical EngineeringForming processesComputer aided optimizationSheet metal formingIndustrial and Manufacturing EngineeringComputer Science ApplicationsReduction (complexity)Function approximationControl and Systems Engineeringvisual_artKey (cryptography)visual_art.visual_art_mediumZoomMoving least squaresMoving least squares methodologySheet metalbusinessSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneSoftware
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An interactive multi-objective approach to heat exchanger network synthesis

2010

In this work we present a multi-objective approach to heat exchanger network synthesis. The approach solves a modified version of the Synheat model using an interactive multi-objective optimisation method, NIMBUS, which is implemented in GAMS. The results obtained demonstrate the potential of interactive multi-objective optimisation.

Mathematical optimizationEngineeringWork (thermodynamics)business.industryGeneral Chemical EngineeringHeat exchanger network synthesisObjective approachbusinessComputer Science ApplicationsComputers & Chemical Engineering
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