Search results for "Sensitivity analysi"

showing 10 items of 110 documents

Using SMAA-2 method with dependent uncertainties for strategic forest planning

2006

Abstract Uncertainty included in forest variables is normally ignored in forest management planning. When the uncertainty is accounted for, it is typically assumed to be independently distributed for the criteria measurements of different alternatives. In forest management planning, the factors introducing the uncertainty can be classified into three main sources: the errors in the basic forestry data, the uncertainty of the (relative) future prices of timber, and the uncertainty in predicting the forest development. Due to the nature of these error sources, most of the involved uncertainties can be assumed to be positively correlated across the alternative management plans and/or criteria.…

Forest planningEconomics and EconometricsDecision support system021103 operations researchSociology and Political ScienceComputer scienceDependency informationbusiness.industry020209 energyEnvironmental resource management0211 other engineering and technologiesForestryMultivariate normal distribution02 engineering and technology15. Life on landManagement Monitoring Policy and LawForest development0202 electrical engineering electronic engineering information engineeringEconometricsSensitivity analysisbusinessForest management planningUncertainty analysisForest Policy and Economics
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Identification and Robust Control of a Quadratic DC/DC Boost Converter by Hammerstein Model

2015

This paper deals with the theoretical framework definition and the experimental application of the Hammerstein (HM) identification and related robust control technique to a quadratic dc/dc single-switch boost (Q-boost) converter. A set of fourth-order transfer functions (TFs) has been identified with the Hammerstein approach, on the basis of a pseudorandom-binary-sequence (PRBS) excitation signal. The set of identified TFs has been then used to design a suitable robust control technique, able to properly deal with the converter parameter uncertainty and load variations. The proposed approach has been tested in numerical simulation and validated experimentally on a suitably developed test se…

Forward converterEngineeringsensitivity analysis.Flyback converterbusiness.industryHammerstein identificationĆuk converterHammerstein approachquadratic dc/dc boost (Q-boost) converterQuadratic DC/DC boost converter sensitivity analysis Hammerstein approach robust control uncertaintyPseudorandom binary sequenceTransfer functionIndustrial and Manufacturing EngineeringQuadratic equationSettore ING-INF/04 - Automaticasensitivity analysisControl and Systems EngineeringControl theoryBoost converterquadratic DC/DC boost converterSensitivity (control systems)Electrical and Electronic EngineeringRobust controlbusinessrobust control
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Parameter identification for heterogeneous materials by optimal control approach with flux cost functionals

2021

The paper deals with the identification of material parameters characterizing components in heterogeneous geocomposites provided that the interfaces separating different materials are known. We use the optimal control approach with flux type cost functionals. Since solutions to the respective state problems are not regular, in general, the original cost functionals are expressed in terms of integrals over the computational domain using the Green formula. We prove the existence of solutions to the optimal control problem and establish convergence results for appropriately defined discretizations. The rest of the paper is devoted to computational aspects, in particular how to handle high sens…

General Computer ScienceComputer scienceFlux010103 numerical & computational mathematicsType (model theory)01 natural sciencesTheoretical Computer ScienceDomain (software engineering)sensitivity analysisConvergence (routing)Applied mathematicsSensitivity (control systems)0101 mathematicskomposiititosittaisdifferentiaaliyhtälötNumerical AnalysisApplied Mathematicsidentification of conductivity coefficientsState (functional analysis)matemaattinen optimointiOptimal control010101 applied mathematicsIdentification (information)säätöteoriaModeling and Simulationnumeerinen analyysioptimal control of PDEs
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Bayesian correlated models for assessing the prevalence of viruses in organic and non-organic agroecosystems

2017

Cultivation of horticultural species under organic management has increased in importance in recent years. However, the sustainability of this new production method needs to be supported by scientific research, especially in the field of virology. We studied the prevalence of three important virus diseases in agroecosystems with regard to its management system: organic versus non-organic, with and without greenhouse. Prevalence was assessed by means of a Bayesian correlated binary model which connects the risk of infection of each virus within the same plot and was defined in terms of a logit generalized linear mixed model (GLMM). Model robustness was checked through a sensitivity analysis …

Hellinger distancesensitivity analysisHellinger distance model robustness risk infection sensitivity analysis virus epidemiology:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]:62 Statistics::62F Parametric inference [Classificació AMS]:62 Statistics::62J Linear inference regression [Classificació AMS]model robustnessvirus epidemiology:62 Statistics::62P Applications [Classificació AMS]62-07 62F15 62J12 62P10 62P12risk infectionSORT- Statistics and Operations Research Transactions
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Sensitivity of scope modelled GPP and fluorescence for different plant functional types

2014

This study addresses the question which factors are responsible for reported positive correlations between solar induced fluorescence (SIF) and gross primary production (GPP). A sensitivity analysis of the model SCOPE, which simulates photosynthesis, fluorescence emission and radiative transfer in canopies, has been carried out for four different plant functional types (PFT): tropical rainforest, C4 crops, C3 crops, and tundra, located in distinct climate zones: tropical everwet (Af), tropical with seasonal drought (savannah, Aw), temperate (Cf), and continental tundra (Dfd). Literature values for structural and physiological parameters and climate reanalysis data were used as input. The ef…

HydrologyIrradianceTropicsHumidityPrimary productionsensitivity analysiAtmospheric sciencesPhotosynthesisgross primary productionTundraSCOPESignal ProcessingTemperate climateEnvironmental sciencefluorescenceplant functional typeTropical rainforest1707
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Micropollutants throughout an integrated urban drainage model: Sensitivity and uncertainty analysis

2017

Abstract The paper presents the sensitivity and uncertainty analysis of an integrated urban drainage model which includes micropollutants. Specifically, a bespoke integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole – SMX). The model takes into account also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Overall, five scenarios, each characterized by different uncertainty combinations of sub-systems (i.e…

HydrologyMathematical modellingSettore ICAR/03 - Ingegneria Sanitaria-Ambientale0208 environmental biotechnologyContaminants of emerging concerns; Mathematical modelling; Monte Carlo simulations; Sensitivity analysis; Urban water quality; Water Science and TechnologyUrban water qualityEnvironmental engineering02 engineering and technologySorption coefficient010501 environmental sciences01 natural sciencesContaminants of emerging concern020801 environmental engineeringKey factorsWater bodySensitivity analysiEnvironmental scienceSewage treatmentSensitivity (control systems)DrainageMonte Carlo simulationUncertainty analysisUncertainty reduction theory0105 earth and related environmental sciencesWater Science and TechnologyJournal of Hydrology
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Uncertainty in water quality modelling: The applicability of Variance Decomposition Approach

2010

Quantification of uncertainty is of paramount interest in integrated urban drainage water quality modelling. Indeed, the assessment of the reliability of the results of complex water quality models is crucial in understanding their significance. However, the state of knowledge regarding uncertainties in urban drainage models is poor. In the case of integrated urban drainage water quality models, due to the fact that integrated approaches are basically a cascade of sub-models (simulating the sewer system, wastewater treatment plant and receiving water body), uncertainty produced in one sub-model propagates to the following ones in a manner dependent on the model structure, the estimation of …

HydrologyMathematical optimizationPropagation of uncertaintyANOVASettore ICAR/03 - Ingegneria Sanitaria-AmbientaleVariance decompositionSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaUncertainty analysiWater quality modellingHydrology (agriculture)Sensitivity analysiVariance decomposition of forecast errorsDecomposition (computer science)Environmental scienceSensitivity analysisDrainageUncertainty analysisWater Science and Technology
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Bayesian approach for uncertainty quantification in water quality modelling: The influence of prior distribution

2010

Summary Mathematical models are of common use in urban drainage, and they are increasingly being applied to support decisions about design and alternative management strategies. In this context, uncertainty analysis is of undoubted necessity in urban drainage modelling. However, despite the crucial role played by uncertainty quantification, several methodological aspects need to be clarified and deserve further investigation, especially in water quality modelling. One of them is related to the “a priori” hypotheses involved in the uncertainty analysis. Such hypotheses are usually condensed in “a priori” distributions assessing the most likely values for model parameters. This paper explores…

HydrologySettore ICAR/03 - Ingegneria Sanitaria-AmbientaleComputer scienceBayesian approachUrban stormwater quality modellingContext (language use)Water quality modellingPrior knowledgeData qualityBayesian approach; Prior knowledge; Uncertainty assessment; Urban stormwater quality modellingPrior probabilityEconometricsSensitivity analysisUncertainty assessmentUncertainty quantificationUncertainty analysisReliability (statistics)Water Science and Technology
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Uncertainty in sewer sediment deposit modelling: detailed vs simplified modelling approaches.

2012

Abstract The paper presents the results of a study in which the uncertainty levels associated with a detailed and a simplified/parsimonious sewer sediment modelling approach have been compared. The detailed approach used an Infoworks CS sewer network model combined with a user developed sediment transport code and the simplified approach used a conceptual sewer flow and quality model. The two approaches have been applied to a single case study sewer network and the simulation results compared. The case study was selected as moderate storm events had occurred during a 2 year rainfall and sewer flow monitoring period. Flooding had been observed and this was thought to be caused by significant…

HydrologyUncertainty Monte carlo SensitivityEngineeringMathematical modelsScale (ratio)Mathematical modelSettore ICAR/03 - Ingegneria Sanitaria-Ambientalebusiness.industryMonte Carlo methodFlow (psychology)Settore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaSedimentCivil engineeringGeophysicsWater qualityGeochemistry and PetrologySewer sedimentSensitivity analysibusinessSediment transportUncertainty analysisNetwork model
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Water quality modelling for ephemeral rivers: Model development and parameter assessment

2010

Summary River water quality models can be valuable tools for the assessment and management of receiving water body quality. However, such water quality models require accurate model calibration in order to specify model parameters. Reliable model calibration requires an extensive array of water quality data that are generally rare and resource-intensive, both economically and in terms of human resources, to collect. In the case of small rivers, such data are scarce due to the fact that these rivers are generally considered too insignificant, from a practical and economic viewpoint, to justify the investment of such considerable time and resources. As a consequence, the literature contains v…

Hydrologygeographygeography.geographical_feature_categorySettore ICAR/03 - Ingegneria Sanitaria-AmbientaleModel parameter assessmentEphemeral keymedia_common.quotation_subjectSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaDrainage basinWater quality modellingRiver water qualityWater resourcesField campaignHydrology (agriculture)Data qualityEnvironmental scienceQuality (business)Water qualitySensitivity analysisWater Science and Technologymedia_commonJournal of Hydrology
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