Search results for "General Computer Science"

showing 10 items of 895 documents

Constructing adaptive generalized polynomial chaos method to measure the uncertainty in continuous models: A computational approach

2015

Due to errors in measurements and inherent variability in the quantities of interest, models based on random differential equations give more realistic results than their deterministic counterpart. The generalized polynomial chaos (gPC) is a powerful technique used to approximate the solution of these equations when the random inputs follow standard probability distributions. But in many cases these random inputs do not have a standard probability distribution. In this paper, we present a step-by-step constructive methodology to implement directly a useful version of adaptive gPC for arbitrary distributions, extending the applicability of the gPC. The paper mainly focuses on the computation…

Numerical AnalysisMathematical optimizationPolynomial chaosGeneral Computer ScienceDifferential equationApplied MathematicsComputingConstructiveMeasure (mathematics)Theoretical Computer ScienceCHAOS (operating system)Generalized polynomialRandom differential equationsModeling and SimulationConvergence (routing)Applied mathematicsProbability distributionMATEMATICA APLICADAAdaptive polynomial chaosMathematics
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Multivariate exponential smoothing: A Bayesian forecast approach based on simulation

2009

This paper deals with the prediction of time series with correlated errors at each time point using a Bayesian forecast approach based on the multivariate Holt-Winters model. Assuming that each of the univariate time series comes from the univariate Holt-Winters model, all of them sharing a common structure, the multivariate Holt-Winters model can be formulated as a traditional multivariate regression model. This formulation facilitates obtaining the posterior distribution of the model parameters, which is not analytically tractable: simulation is needed. An acceptance sampling procedure is used in order to obtain a sample from this posterior distribution. Using Monte Carlo integration the …

Numerical AnalysisMultivariate statisticsGeneral Computer ScienceApplied MathematicsUnivariateMarkov chain Monte CarloTheoretical Computer ScienceNormal-Wishart distributionsymbols.namesakeUnivariate distributionModeling and SimulationStatisticssymbolsMultivariate t-distributionBayesian linear regressionGibbs samplingMathematicsMathematics and Computers in Simulation
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On the reconstruction of discontinuous functions using multiquadric RBF–WENO local interpolation techniques

2020

Abstract We discuss several approaches involving the reconstruction of discontinuous one-dimensional functions using parameter-dependent multiquadric radial basis function (MQ-RBF) local interpolants combined with weighted essentially non-oscillatory (WENO) techniques, both in the computation of the locally optimized shape parameter and in the combination of RBF interpolants. We examine the accuracy of the proposed reconstruction techniques in smooth regions and their ability to avoid Gibbs phenomena close to discontinuities. In this paper, we propose a true MQ-RBF–WENO method that does not revert to the classical polynomial WENO approximation near discontinuities, as opposed to what was pr…

Numerical AnalysisPolynomialLocal multiquadric radial basis function (RBF) interpolationAdaptive parameterGeneral Computer ScienceApplied MathematicsComputationJump discontinuityClassification of discontinuitiesShape parameterTheoretical Computer ScienceApproximation orderGibbs phenomenonMAT/08 - ANALISI NUMERICAsymbols.namesakeWeighted Essentially Non-Oscillatory (WENO) interpolationModeling and SimulationsymbolsApplied mathematicsRadial basis functionMathematicsInterpolation
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Reprint of: Approximate Taylor methods for ODEs

2018

Abstract A new method for the numerical solution of ODEs is presented. This approach is based on an approximate formulation of the Taylor methods that has a much easier implementation than the original Taylor methods, since only the functions in the ODEs, and not their derivatives, are needed, just as in classical Runge–Kutta schemes. Compared to Runge–Kutta methods, the number of function evaluations to achieve a given order is higher, however with the present procedure it is much easier to produce arbitrary high-order schemes, which may be important in some applications. In many cases the new approach leads to an asymptotically lower computational cost when compared to the Taylor expansio…

ODE integratorsGeneral Computer ScienceTaylor methodsMathematicsofComputing_NUMERICALANALYSISGeneral EngineeringOdeFunction (mathematics)Present procedure01 natural sciences010101 applied mathematicsFaà di Bruno's formulasymbols.namesakeTaylor seriessymbolsApplied mathematicsOrder (group theory)0101 mathematicsMathematicsComputers & Fluids
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Mathematical Modelling of Leukemia Treatment

2021

Leukemia is a cancer that can be treated in a variety of ways: chemotherapy, radiation therapy and stem cell transplant. Recovery rates for this disease are relatively high, the treatment itself has a painful effect on the body and is accompanied by numerous side effects that can persist years after the patient is cured. For this reason, efforts are underway worldwide to develop more selective therapies that will only affect leukemia cells and not healthy cells. Knowledge of developmental GRN is yet scarce, and it is early for a systematic comparative effort. We consider mathematical model of genetic regulatory networks. This model consists of a nonlinear system of ordinary differential equ…

Oncologymedicine.medical_specialtyLeukemiaGeneral Computer ScienceComputer scienceInternal medicinemedicinemedicine.diseaseResearch dataWSEAS TRANSACTIONS ON COMPUTERS
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Spreading dynamics of three-dimensional droplets by the lattice-Boltzmann method

2000

Abstract We have simulated spreading of small droplets on smooth and rough solid surfaces using the three-dimensional lattice-Boltzmann method. We present results for the influence of the initial distance and shape of the drop from the surface on scaling of droplet radius R as a function of time. For relatively flat initial drop shapes our observations are consistent with Tanner's law R ∼ t q , where q =1/10. For increasingly spherical initial shapes, the exponent q increases rapidly being above one half for spherical droplets initially just above the surface. As expected, surface roughness slows down spreading, decreases the final drop radius, and results in irregular droplet shape due to …

One halfGeneral Computer ScienceChemistryDrop (liquid)Lattice Boltzmann methodsGeneral Physics and AstronomyWettingGeneral ChemistryMechanicsSurface finishBoltzmann equationPhysics::Fluid DynamicsDropletComputational MathematicsClassical mechanicsMechanics of MaterialsSurface roughnessGeneral Materials ScienceWettingScalingLattice-Boltzmann
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Surface-Impedance Formulation for Hollow-Core Waveguides Based on Subwavelength Gratings

2022

A rigorous Surface Impedance (SI) formulation for planar waveguides is presented. This modal technique splits the modal analysis of the waveguide in two steps. First, we obtain the modes characteristic equations as a function of the SI and, second, we need to obtain the surface impedance values using either analytical or numerical methods. We validate the technique by comparison with well-known analytical cases: the parallel-plate waveguide with losses and the dielectric slab waveguide. Then, we analyze an optical hollow-core waveguide de ned by two high-contrast subwavelength gratings validating our results by comparison with reported values. Finally, we show the potential of our formulati…

Ones electromagnètiquesGeneral Computer ScienceGeneral EngineeringPhysics::OpticsGeneral Materials ScienceÒpticaMaterialsIEEE Access
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Interactive multiobjective optimization system WWW-NIMBUS on the Internet

2000

Abstract NIMBUS is a multiobjective optimization method capable of solving nondifferentiable and nonconvex problems. We describe the NIMBUS algorithm and its implementation WWW-NIMBUS. To our knowledge WWW-NIMBUS is the first interactive multiobjective optimization system on the Internet. The main principles of its implementation are centralized computing and a distributed interface. Typically, the delivery and update of any software is problematic. Limited computer capacity may also be a problem. Via the Internet, there is only one version of the software to be updated and any client computer has the capabilities of a server computer. Further, the World-Wide Web (WWW) provides a graphical …

Optimization problemGeneral Computer ScienceComputer sciencebusiness.industryInterface (computing)Distributed computingClientManagement Science and Operations ResearchMulti-objective optimizationSoftwareModeling and SimulationServerThe InternetbusinessGraphical user interfaceComputers & Operations Research
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Heuristics for solving the parameter tuning problem in motion cueing algorithms.

2017

[ES] Diversos tipos de plataformas robóticas son empleadas habitualmente para la generación de claves gravito-inerciales en simuladores. Además del control de los actuadores, dichas plataformas deben ejecutar complejos algoritmos de control conocidos como algoritmos de washout, que deben ser ajustados para que el movimiento generado sea similar al simulado. El ajuste de dichos algoritmos es complejo por el elevado número de parámetros que poseen. Además, dicho ajuste se ha venido realizando tradicionalmente de modo manual mediante evaluaciones subjetivas. En este trabajo, los autores proponen un método automático de ajuste basado en optimización heurística, métricas objetivas, y simulación …

Optimization0209 industrial biotechnologyEngineeringGeneral Computer ScienceMotion cueing algorithmsHeuristic (computer science)02 engineering and technologyTuningOptimizaciónMotion (physics)03 medical and health sciences020901 industrial engineering & automation0302 clinical medicineGenetic algorithmIn vehicleHeuristicsMotion platformsbusiness.industryRoboticsAlgoritmos de controlHeurísticasControl and Systems EngineeringAjuste de parámetrosArtificial intelligencebusinessRobóticaSimuladores030217 neurology & neurosurgerySimulationPlataformas de movimiento
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A methodology for the semi-automatic generation of analytical models in manufacturing

2018

International audience; Advanced analytics can enable manufacturing engineers to improve product quality and achieve equipment and resource efficiency gains using large amounts of data collected during manufacturing. Manufacturing engineers, however, often lack the expertise to apply advanced analytics, relying instead on frequent consultations with data scientists. Furthermore, collaborations between manufacturing engineers and data scientists have resulted in highly specialized applications that are not relevant to broader use cases. The manufacturing industry can benefit from the techniques applied in these collaborations if they can be generalized for a wide range of manufacturing probl…

Optimization0209 industrial biotechnologySupport Vector MachineGeneral Computer ScienceProcess (engineering)Computer sciencemedia_common.quotation_subjectResource efficiencyComputerApplications_COMPUTERSINOTHERSYSTEMS02 engineering and technology020901 industrial engineering & automationManufacturing0202 electrical engineering electronic engineering information engineeringAdvanced analytics[INFO]Computer Science [cs]Quality (business)Use caseMillingmedia_commonGenetic AlgorithmArtificial Neural-Networkbusiness.industrySystemsGeneral EngineeringModel-basedNeural networkRegressionManufacturing engineeringProduct (business)ManufacturingSurface-RoughnessAnalytics020201 artificial intelligence & image processingDynamic Bayesian NetworksPerformance indicatorFault-DiagnosisPredictionbusinessComputers in Industry
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