Search results for "parameter"

showing 10 items of 14056 documents

An improved sampling strategy based on trajectory design for application of the Morris method to systems with many input factors

2012

[EN] In this paper, a revised version of the Morris approach, which includes an improved sampling strategy based on trajectory design, has been adapted to the screening of the most influential parameters of a fuzzy controller applied to WWTPs. Due to the high number of parameters, a systematic approach has been proposed to apply this improved sampling strategy with low computational demand. In order to find out the proper repetition number of elementary effects of each input factor on model output (EEi) calculations, an iterative and automatic procedure has been applied. The results show that the sampling strategy has a significant effect on the parameter significance ranking and that rando…

Mathematical optimizationEnvironmental EngineeringComputer scienceEcological ModelingFuzzy controllersSampling (statistics)Parameter spaceRepetition NumberFuzzy logicSampling strategyRankingControl theoryTrajectoryMorris methodMorris screeningSensitivity analysisSoftwareTECNOLOGIA DEL MEDIO AMBIENTE
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Stochastic dynamics of linear elastic trusses in presence of structural uncertainties (virtual distortion approach)

2004

Structures involving uncertainties in material and/or in geometrical parameters are referred to as uncertain structures. Reliability analysis of such structures strongly depends on variation of parameters and probabilistic approach is often used to characterize structural uncertainties. In this paper dynamic analysis of linearly elastic system in presence of random parameter variations will be performed. In detail parameter fluctuations have been considered as inelastic, stress and parameter dependent superimposed strains. Analysis is then carried out via superposition principle accounting for response to external agencies and parameter dependent strains. Proposed method yields asymptotic s…

Mathematical optimizationMechanical EngineeringLinear elasticityAerospace EngineeringTrussOcean EngineeringStatistical and Nonlinear PhysicsCondensed Matter PhysicsVariation of parametersDynamic load testingSuperposition principleVirtual DistortionNuclear Energy and EngineeringDynamic AnalysiSuperposition PrincipleDistortionStochastic ParameterConvergence (routing)Statistical physicsAsymptotic expansionCivil and Structural EngineeringMathematicsProbabilistic Engineering Mechanics
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Robust estimation of partial directed coherence by the vector optimal parameter search algorithm

2009

We propose a method for the accurate estimation of Partial Directed Coherence (PDC) from multichannel time series. The method is based on multivariate vector autoregressive (MVAR) model identification performed through the recently proposed Vector Optimal Parameter Search (VOPS) algorithm. Using Monte Carlo simulations generated by different MVAR models, the proposed VOPS algorithm is compared with the traditional Vector Least Squares (VLS) identification method. We show that the VOPS provides more accurate PDC estimates than the VLS (either overall and single-arc errors) in presence of interactions with long delays and missing terms, and for noisy multichannel time series. ©2009 IEEE.

Mathematical optimizationMultivariate statisticsNeuroscience (all)Parameter search algorithmComputer scienceEstimation theoryMonte Carlo methodSystem identificationPartial directed coherenceBiomedical EngineeringAC powerAutoregressive modelSearch algorithmVector autoregressive modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCoherence (signal processing)Brain connectivityNeurology (clinical)Algorithm
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Simultaneous Airline Scheduling

2008

Currently, there are no solution approaches available to construct and optimize airline schedules within a single model. All existing approaches decompose the problem into smaller and less complex subproblems and solve those subproblems separately. This chapter presents a metaheuristic for simultaneous airline scheduling where several different subproblems are integrated into one single optimization model, except for crew scheduling. The problem-specific metaheuristic uses an adaptive procedure for operator selection to allow an efficient choice between a variety of different operators. Experiments are conducted as proof-of-concept and to calibrate free parameters. Comparing different searc…

Mathematical optimizationOperator (computer programming)Single modelJob shop schedulingComputer scienceScheduling (production processes)MetaheuristicCrew schedulingAdaptive procedureFree parameter
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Wideband impedance matrix representation of passive waveguide components based on cascaded planar junctions

2009

[1] A very efficient technique for the full-wave analysis of passive waveguide components, composed of the cascade connection of planar junctions, is presented. This novel technique provides the wideband generalized impedance matrix representation of the whole structure in the form of pole expansions, thus extracting the most expensive computations from the frequency loop. For this purpose, the structure is segmented into planar junctions and uniform waveguide sections, which are characterized in terms of wideband impedance matrices. Then, an efficient iterative algorithm for combining such matrices, and finally providing the wideband generalized impedance matrix of the complete structure, …

Mathematical optimizationWaveguide filterIterative methodCondensed Matter PhysicsImpedance parametersTopologyPlanarCascadeGeneral Earth and Planetary SciencesWaveguide (acoustics)Electrical and Electronic EngineeringWidebandElectrical impedanceMathematicsRadio Science
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Probing non-standard neutrino interactions with supernova neutrinos

2007

17 pages, 12 figures.-- PACS nrs.: 13.15.+g; 14.60.Lm; 14.60.St; 97.60.Bw.-- ISI Article Identifier: 000249786800015.-- ArXiv pre-print available at: http://arxiv.org/abs/0704.0032

Matter densityNuclear and High Energy PhysicsParticle physicsSolar neutrinoAstrophysics::High Energy Astrophysical PhenomenaSolar neutrinosFOS: Physical sciencesElectronStandard ModelScatteringHigh Energy Physics - Phenomenology (hep-ph)Core-collapse supernovaeMassless neutrinosElectroweak parametersNeutrino oscillationEnvelope (waves)PhysicsNeutrino oscillationsHigh Energy Physics::PhenomenologyFísicaSupernovaHigh Energy Physics - PhenomenologyNeutrino detectorResonant amplificationHigh Energy Physics::ExperimentNeutrino
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Experimental study of the pyrolysis of waste bitumen for oil production

2020

Abstract This work focuses on bitumen slow pyrolysis. Mass and energy yields of oil, solid and gas were obtained from pyrolysis experiments using a semi-batch reactor in a nitrogen atmosphere, under three non-isothermal conditions (maximum temperature: 450 °C, 500 °C and 550 °C). The effect of temperature on the product yields was discussed. The gas compositions were analysed using gas chromatography (GC) and the heating value of oil and solid residue was also measured. Using a thermo-gravimetric analyser, kinetic parameters were evaluated through Ozawa-Flynn-Wall (OFW) method. Results showed that oil yield is maximum at 500 °C (50%). Moreover, gas yield increased with increasing pyrolysis …

Maximum temperatureMaterials scienceSettore ING-IND/25 - Impianti Chimici020209 energyAnalyserAnalytical chemistryBitumen Kinetic parameters Oil Product yields Pyrolysis Syngas Thermo-gravimetric analysis Waste to fuel02 engineering and technologyKinetic energy020401 chemical engineeringAsphaltOil production0202 electrical engineering electronic engineering information engineeringHeat of combustionGas chromatography0204 chemical engineeringPyrolysisJournal of the Energy Institute
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Use of Guided Regularized Random Forest for Biophysical Parameter Retrieval

2018

This paper introduces a feature selection method based on random forest -the Guided Regularized Random Forest (GRRF)- which can be used in classification and regression tasks. The method is based on the regularization of the information gain in the random forest nodes to obtain a subset of relevant and non-redundant features. The proposed method is used as a preliminary step In the process of retrieving biophysical parameters from a hyperspectral image. Preliminary experiments show that we can reduce the RMSE of the retrievals by around 7% for the Leaf Area Index and around 8% for the fraction of vegetation cover when compared to the results using random forest features.

Mean squared error22/3 OA procedurebusiness.industryComputer scienceFeature extractionHyperspectral images0211 other engineering and technologiesHyperspectral imagingPattern recognitionFeature selection02 engineering and technologyBiophysical parameter retrievalRegularization (mathematics)RegressionRandom forestFeature selection0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceLeaf area indexbusinessRandom forest021101 geological & geomatics engineeringIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Bayesian calibration of the nitrous oxide emission module of an agro-ecosystem model

2008

1. NitroEurope Open Science Conference on Reactive Nitrogen and the European Greenhouse Gas Balance ; Ghent (Belgique) - (2008-02-20 - 2008-02-21) / Conférence; Nitrous oxide (N2O) is the main biogenic greenhouse gas contributing to the global warming potential (GWP) of agro-ecosystems. Evaluating the impact of agriculture on climate therefore requires a capacity to predict N2O emissions in relation to environmental conditions and crop management. Biophysical models simulating the dynamics of carbon and nitrogen in agro-ecosystems have a unique potential to explore these relationships, but are fraught with high uncertainties in their parameters due to their variations over time and space. H…

Mean squared error[SDE.MCG]Environmental Sciences/Global ChangesBayesian probabilityparameter uncertainty010501 environmental sciencesAtmospheric sciences7. Clean energy01 natural sciencesEcology and Environment[ SDV.EE ] Life Sciences [q-bio]/Ecology environmentsymbols.namesake[STAT.AP] Statistics [stat]/Applications [stat.AP]Ecosystem modelgreenhouse gasesMarkov Chain Monte Carlo0105 earth and related environmental sciences2. Zero hunger[SDV.EE]Life Sciences [q-bio]/Ecology environment[STAT.AP]Statistics [stat]/Applications [stat.AP]EcologyMarkov chainnitrous oxideEcology[ STAT.AP ] Statistics [stat]/Applications [stat.AP]Global warmingMarkov chain Monte Carlo04 agricultural and veterinary sciences15. Life on land[ SDE.MCG ] Environmental Sciences/Global Changes[SDV.EE] Life Sciences [q-bio]/Ecology environment[SDE.MCG] Environmental Sciences/Global ChangesAgriculture and Soil Science13. Climate actionGreenhouse gas040103 agronomy & agriculturesymbols0401 agriculture forestry and fisheriesEnvironmental scienceProbability distributionAnimal Science and ZoologyCERES-EGCAgronomy and Crop Sciencebayesian calibration
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Identification of linear parameter varying models

2002

We consider identification of a certain class of discrete-time nonlinear systems known as linear parameter varying system. We assume that inputs, outputs and the scheduling parameters are directly measured, and a form of the functional dependence of the system coefficients on the parameters is known. We show how this identification problem can be reduced to a linear regression, and provide compact formulae for the corresponding least mean square and recursive least-squares algorithms. We derive conditions on persistency of excitation in terms of the inputs and scheduling parameter trajectories when the functional dependence is of polynomial type. These conditions have a natural polynomial i…

Mechanical EngineeringGeneral Chemical EngineeringBiomedical EngineeringAerospace EngineeringIndustrial and Manufacturing EngineeringPolynomial interpolationScheduling (computing)Parameter identification problemLeast mean squares filterNonlinear systemControl and Systems EngineeringControl theoryLinear regressionApplied mathematicsElectrical and Electronic EngineeringMathematicsInternational Journal of Robust and Nonlinear Control
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