Search results for "post-processing"

showing 4 items of 4 documents

On a global superconvergence of the gradient of linear triangular elements

1987

Abstract We study a simple superconvergent scheme which recovers the gradient when solving a second-order elliptic problem in the plane by the usual linear elements. The recovered gradient globally approximates the true gradient even by one order of accuracy higher in the L 2 -norm than the piecewise constant gradient of the Ritz—Galerkin solution. A superconvergent approximation to the boundary flux is presented as well.

Applied MathematicsMathematical analysisOrder of accuracySuperconvergenceglobal superconvergence for the gradientComputer Science::Numerical AnalysisGlobal superconvergence for the gradientMathematics::Numerical AnalysisNonlinear conjugate gradient methodElliptic curveComputational Mathematicserror estimatesNorm (mathematics)boundary fluxPiecewisepost-processing of the Ritz—Galerkin schemeGradient descentGradient methodMathematicsJournal of Computational and Applied Mathematics
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Identification and Handling of Critical Irradiance Forecast Errors Using a Random Forest Scheme – A Case Study for Southern Brazil

2015

Abstract Large forecast errors of solar power prediction cause challenges for the management of electric grids. Here, the classification technique Random Forests is applied to analyze the possible linkage of hourly or daily forecast errors to the actual situation given by a set of meteorological variables. This form a prediction of the forecast error and is thus usable to update the forecast. The performance of this scheme is assessed for the example of irradiance forecasts in Brazil. While limited to none improvements are obtained for next-hour forecasts, significant improvements are obtained for the next-day forecasts.

Meteorologybusiness.industryComputer sciencepost-processingIrradianceLinkage (mechanical)Forecast verificationRandom forestlaw.inventionSet (abstract data type)Identification (information)Energy(all)lawsolar irradiance forecastsbusinessConsensus forecastRandom Forest classificationSolar powerEnergy Procedia
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Approximate Bayesian Computation for Forecasting in Hydrological models

2018

Approximate Bayesian Computation (ABC) is a statistical tool for handling parameter inference in a range of challenging statistical problems, mostly characterized by an intractable likelihood function. In this paper, we focus on the application of ABC to hydrological models, not as a tool for parametric inference, but as a mechanism for generating probabilistic forecasts. This mechanism is referred as Approximate Bayesian Forecasting (ABF). The abcd water balance model is applied to a case study on Aipe river basin in Columbia to demonstrate the applicability of ABF. The predictivity of the ABF is compared with the predictivity of the MCMC algorithm. The results show that the ABF method as …

Predictive uncertainty Probabilistic post-processing approach Bayesian forecasting Sufficient statistics Hydrological models Intractable likelihood
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EXPERIMENTAL INVESTIGATION OF DILUTE SOLID-LIQUID SUSPENSION IN AN UNBAFFLED STIRRED VESSELS BY A NOVEL PULSED LASER BASED IMAGE ANALYSIS TECHNIQUE

2009

The availability of experimental information on solid distribution inside stirred tanks is a topic of great importance in several industrial applications. The measurement of solid particle distribution in turbulent multiphase flow is not simple and the development of suitable measurement techniques is still in progress. In this work a novel non-intrusive technique for measuring particle concentration fields in solid-liquid systems is employed. The technique makes use of a laser sheet, a high sensitivity digital camera for image acquisition and a Matlab procedure for post-processing the acquired images. Experimental data are here obtained for the case of an unbaffled stirred tank. Stable tor…

lcsh:Computer engineering. Computer hardwareSettore ING-IND/25 - Impianti Chimicilcsh:TP155-156lcsh:TK7885-7895lcsh:Chemical engineeringThe availability of experimental information on solid distribution inside stirred tanks is a topic of great importance in several industrial applications. The measurement of solid particle distribution in turbulent multiphase flow is not simple and the development of suitable measurement techniques is still in progress. In this work a novel non-intrusive technique for measuring particle concentration fields in solid-liquid systems is employed. The technique makes use of a laser sheet a high sensitivity digital camera for image acquisition and a Matlab procedure for post-processing the acquired images. Experimental data are here obtained for the case of an unbaffled stirred tank. Stable toroidal attractors for particles are observed under given circumstances. Their existence consistency and extension depends on particle type fluid properties tank geometry and impeller velocity.Chemical Engineering Transactions
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