Search results for " Regression"

showing 10 items of 1835 documents

Machine Learning Regression Approaches for Colored Dissolved Organic Matter (CDOM) Retrieval with S2-MSI and S3-OLCI Simulated Data

2018

The colored dissolved organic matter (CDOM) variable is the standard measure of humic substance in waters optics. CDOM is optically characterized by its spectral absorption coefficient, a C D O M at at reference wavelength (e.g., ≈ 440 nm). Retrieval of CDOM is traditionally done using bio-optical models. As an alternative, this paper presents a comparison of five machine learning methods applied to Sentinel-2 and Sentinel-3 simulated reflectance ( R r s ) data for the retrieval of CDOM: regularized linear regression (RLR), random forest regression (RFR), kernel ridge regression (KRR), Gaussian process regression (GPR) and support vector machines (SVR). Two different datasets of radiative t…

Polynomial regression010504 meteorology & atmospheric sciencesArtificial neural networkbusiness.industry0211 other engineering and technologiesta117102 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesremote sensing; CDOM; optically complex waters; linear regression; machine learning; Sentinel 2; Sentinel 3RegressionRandom forestSupport vector machineColored dissolved organic matterKrigingLinear regressionGeneral Earth and Planetary SciencesArtificial intelligencebusinesscomputer021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote Sensing
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Correcting AVHRR Long Term Data Record V3 estimated LST from orbital drift effects

2012

Abstract NOAA (National Oceanic and Atmospheric Administration) satellite series is known to suffer from what is known as the orbital drift effect. The Long Term Data Record (LTDR [Pedelty et al., 2007]), which provides AVHRR (Advanced Very High Resolution Radiometer) data from these satellites for the 80s and the 90s, is also affected by this orbital drift. To correct this effect on Land Surface Temperature (LST) time series, a novel method is presented here, which consists in adjusting retrieved LST time series on the basis of statistical information extracted from the time series themselves. This method is as simple and straightforward as possible, in order to be implemented easily for s…

Polynomial regression010504 meteorology & atmospheric sciencesBasis (linear algebra)Series (mathematics)PixelAdvanced very-high-resolution radiometer0211 other engineering and technologiesSoil ScienceGeology02 engineering and technologyResidual01 natural sciences13. Climate actionEnvironmental scienceSatelliteComputers in Earth SciencesChange detection021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Relationship between UVB and broadband solar radiation in Spain

2014

The daily values of UVB irradiation (290–315 nm), IUVB, and the broadband total irradiation (300–2800 nm), IT, measured on a horizontal plane have been correlated for the period 2000–2008 at 16 measurement sites in Spain. The results have been compared with the daily experimental values registered at the same sites during the period 2009–2011. The coefficients of determination R2 obtained by applying a linear regression are higher than 0.88 for all sites and increase to 0.94 when using a quadratic regression. When all data are considered together, the values of R2 are 0.91 and 0.97 for the linear and quadratic regressions, respectively. Three different clearness indices, which are dimension…

Polynomial regressionAtmospheric ScienceCoefficient of determinationMean squared errorMeteorologyClimatologyLinear regressionSolar zenith angleRadiationAtmospheric sciencesLatitudeMathematicsDimensionless quantityInternational Journal of Climatology
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Formulation and test of an ice aggregation scheme for two-moment bulk microphysics schemes

2013

A simple formulation of aggregation for 2-moment bulk microphysical models is de-rived. The solution involves the evaluation of a double integral of the collection kernelweighted with the crystal size (or mass) distribution. This quantity is to be inserted intothe differential equation for the crystal number concentration which has classical form. The double integrals are evaluated numerically for log-normal size distributions overa large range of geometric mean masses. A polynomial fit of the results is given thatyields good accuracy. Various tests of the new parameterization are described: aggre-gation as stand-alone process, in a box-model, and in 2-D simulations of a cirrostratuscloud. …

Polynomial regressionAtmospheric ScienceMicrophysicsDifferential equationChemistryMultiple integralZirrenlcsh:QC1-999WolkenmikrophysikMoment (mathematics)lcsh:ChemistryAggregationDistribution (mathematics)Classical mechanicslcsh:QD1-999Kernel (statistics)ModelleCirrusDynamik der AtmosphäreStatistical physicsEiskristallelcsh:PhysicsAtmospheric Chemistry and Physics
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Cell-average multiresolution based on local polynomial regression. Application to image processing

2014

In Harten (1996) [32] presented a general framework about multiresolution representation based on four principal operators: decimation and prediction, discretization and reconstruction. The discretization operator indicates the nature of the data. In this work the pixels of a digital image are obtained as the average of a function in some defined cells. A family of Harten cell-average multiresolution schemes based on local polynomial regression is presented. The stability is ensured by the linearity of the operators obtained and the order is calculated. Some numerical experiments are performed testing the accuracy of the prediction operators in comparison with the classical linear and nonli…

Polynomial regressionComputational MathematicsDecimationMathematical optimizationDigital imageOperator (computer programming)Kernel methodDiscretizationApplied MathematicsLinearityImage processingAlgorithmMathematicsApplied Mathematics and Computation
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Non-separable local polynomial regression cell-average multiresolution operators. Application to compression of images

2016

Abstract Cell-average multiresolution Harten׳s algorithms have been satisfactorily used to compress data. These schemes are based on two operators: decimation and prediction. The accuracy of the method depends on the prediction operator. In order to design a precise function, local polynomial regression has been used in the last years. This paper is devoted to construct a family of non-separable two-dimensional linear prediction operators approximating the real values with this procedure. Some properties are proved as the order of the scheme and the stability. Some numerical experiments are performed comparing the new methods with the classical linear method.

Polynomial regressionDecimationMathematical optimizationComputer Networks and CommunicationsApplied Mathematics020206 networking & telecommunicationsLinear prediction010103 numerical & computational mathematics02 engineering and technologyFunction (mathematics)01 natural sciencesStability (probability)Separable spaceOperator (computer programming)Control and Systems EngineeringCompression (functional analysis)Signal Processing0202 electrical engineering electronic engineering information engineering0101 mathematicsAlgorithmMathematicsJournal of the Franklin Institute
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Non-linear Local Polynomial Regression Multiresolution Methods Using $$\ell ^1$$-norm Minimization with Application to Signal Processing

2015

Harten’s Multiresolution has been developed and used for different applications such as fast algorithms for solving linear equations or compression, denoising and inpainting signals. These schemes are based on two principal operators: decimation and prediction. The goal of this paper is to construct an accurate prediction operator that approximates the real values of the signal by a polynomial and estimates the error using \(\ell ^1\)-norm in each point. The result is a non-linear multiresolution method. The order of the operator is calculated. The stability of the schemes is ensured by using a special error control technique. Some numerical tests are performed comparing the new method with…

Polynomial regressionDecimationMathematical optimizationSignal processingPolynomialOperator (computer programming)Computer scienceCompression (functional analysis)InpaintingData_CODINGANDINFORMATIONTHEORYAlgorithmLinear equation
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Non-consistent cell-average multiresolution operators with application to image processing

2016

In recent years different techniques to process signal and image have been designed and developed. In particular, multiresolution representations of data have been studied and used successfully for several applications such as compression, denoising or inpainting. A general framework about multiresolution representation has been presented by Harten (1996) 20. Harten's schemes are based on two operators: decimation, D , and prediction, P , that satisfy the consistency property D P = I , where I is the identity operator. Recently, some new classes of multiresolution operators have been designed using learning statistical tools and weighted local polynomial regression methods obtaining filters…

Polynomial regressionDecimationTheoretical computer scienceApplied MathematicsInpaintingImage processing010103 numerical & computational mathematics01 natural sciences010101 applied mathematicsComputational MathematicsOperator (computer programming)Consistency (statistics)0101 mathematicsRepresentation (mathematics)AlgorithmMathematicsImage compressionApplied Mathematics and Computation
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A Comparison between Three Meta-Modeling Optimization Approaches to Design a Tube Hydroforming Process

2012

Computer aided procedures to design and optimize forming processes have become crucial research topics as the industrial interest in cost and time reduction has been increasing. A standalone numerical simulation approach could make the design too time consuming while meta-modeling techniques enables faster approximation of the investigated phenomena, reducing the simulation time. Many researchers are, nowadays, facing such research challenge by using various approaches. Response surface method (RSM) is probably the most known one, since its effectiveness was demonstrated in the past years. The effectiveness of RSM depends both on the definition of the Design of Experiments (DoE) and the acc…

Polynomial regressionEngineeringHydroformingMathematical optimizationComputer simulationbusiness.industryMechanical EngineeringDesign of experimentsReduction (complexity)Function approximationMechanics of MaterialsKrigingGeneral Materials ScienceMoving least squaresbusinessKey Engineering Materials
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Permutation Tests in Linear Regression

2015

Exact permutation tests are available only in rather simple linear models. The problem is that, although standard assumptions allow permuting the errors of the model, we cannot permute them in practice, because they are unobservable. Nevertheless, the residuals of the model can be permuted. A proof is given here which shows that it is possible to approximate the unobservable permutation distribution where the true errors are permuted by permuting the residuals. It is shown that approximation holds asymptotically and almost surely for certain quadratic statistics as well as for statistics which are expressible as the maximum of appropriate linear functions. The result is applied to testing t…

Polynomial regressionGeneral linear modelHeteroscedasticityPermutationMathematics::CombinatoricsLinear predictor functionStatisticsLinear regressionLinear modelApplied mathematicsSegmented regressionMathematics
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