Search results for "Statistical Model"

showing 10 items of 163 documents

DAE-GP

2020

Estimation of distribution genetic programming (EDA-GP) algorithms are metaheuristics where sampling new solutions from a learned probabilistic model replaces the standard mutation and recombination operators of genetic programming (GP). This paper presents DAE-GP, a new EDA-GP which uses denoising autoencoder long short-term memory networks (DAE-LSTMs) as probabilistic model. DAE-LSTMs are artificial neural networks that first learn the properties of a parent population by mapping promising candidate solutions to a latent space and reconstructing the candidate solutions from the latent space. The trained model is then used to sample new offspring solutions. We show on a generalization of t…

education.field_of_studyArtificial neural networkbusiness.industryComputer scienceOffspringPopulationProbabilistic logicGenetic programmingStatistical model0102 computer and information sciences02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesTree (data structure)Estimation of distribution algorithm010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinesseducationcomputerMetaheuristicProceedings of the 2020 Genetic and Evolutionary Computation Conference
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Influence of geometric variations on LV activation times: A study on an atlas-based virtual population

2010

We present the fully automated pipeline we have developed to obtain electrophysiological simulations of the heart on a large atlas-based virtual population. This virtual population was generated from a statistical model of left ventricular geometry, represented by a surface model. Correspondence between tetrahedralized volumetric meshes was obtained using Thin Plate Spline warps. Simulations are based on the fast solving of Eikonal equations, and stimulation sites correspond to physiological activation. We report variations of total activation time introduced by geometry, as well as variations in the location of last activation. The obtained results suggest that the total activation time ha…

education.field_of_studyAtlas (topology)Eikonal equationPopulationGeometryStatistical modelVolume mesh030204 cardiovascular system & hematology030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineFully automatedLeft ventricular geometryeducationThin plate splineMathematics
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Providing insights into browntail moth local outbreaks by combining life table data and semi-parametric statistics

2011

1. Life table studies have been an essential tool for the comprehension of insect population dynamics, although their use has been methodologically biased by a primary focus on mortality factors, especially natural enemies. Thus, studies in natural populations may relegate important mortality sources to the ‘unknown’ or ‘residual’ mortality categories. To overcome this limitation, life tables may be complemented by combining them with other approaches. 2. The aim of the present study was to provide insights into browntail moth Euproctis chrysorrhoea L. (Lepidoptera: Lymantriidae) local outbreaks by combining life table data and statistical modelling. First, E. chrysorrhoea population densit…

education.field_of_studyEcologyEcologyPopulationOutbreakInferenceStatistical modelBiologyResidualPopulation densitySemiparametric modelHabitatInsect ScienceStatisticseducationEcological Entomology
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Open challenges in environmental data analysis and ecological complex systems (a)

2020

Abstract This letter focuses on open challenges in the fields of environmental data analysis and ecological complex systems. It highlights relations between research problems in stochastic population dynamics, machine learning and big data research, and statistical physics. Recent and current developments in statistical modeling of spatiotemporal data and in population dynamics are briefly reviewed. The presentation emphasizes stochastic fluctuations, including their statistical representation, data-based estimation, prediction, and impact on the physics of the underlying systems. Guided by the common thread of stochasticity, a deeper and improved understanding of environmental processes an…

education.field_of_studyInterdisciplinary applications of physicEcologybusiness.industryEcology (disciplines)PopulationBig dataComplex systemGeneral Physics and AstronomyStatistical modelEcological pattern formationPopulation dynamicData modelingEnvironmental dataEnvironmental studieseducationbusinessEnvironmental studiesEurophysics Letters
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Statistical methods for the evaluation of university systems

2011

educational systemdata assessmentSettore SECS-S/05 - Statistica SocialeComposite indicatorstatistical modeling for educationstudent evaluation teaching
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Evaporation channel as a tool to study fission dynamics

2017

The dynamics of the fission process is expected to affect the evaporation residue cross section because of the fission hindrance due to the nuclear viscosity. Systems of intermediate fissility constitute a suitable environment for testing such hypothesis, since they are characterized by evaporation residue cross sections comparable or larger than the fission ones. Observables related to emitted charged particle, due to their relatively high emission probability, can be used to put stringent constraints on models describing the excited nucleus decay and to recognize the effects of fission dynamics. In this work model simulations are compared with the experimental data collected via the ^{32}…

fission dynamics evaporation residues statistical model dynamical fission modelPhysicsNuclear and High Energy PhysicsFissility010308 nuclear & particles physicsFissionFOS: Physical sciencesFusion fissionObservableStatistical model01 natural sciencesCharged particleNuclear physicsExcited nucleus0103 physical sciencesNuclear Experiment (nucl-ex)Nuclear Experiment010306 general physicsNuclear ExperimentNuclear Physics A
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Estimating finite mixtures of semi-Markov chains: an application to the segmentation of temporal sensory data

2019

Summary In food science, it is of great interest to obtain information about the temporal perception of aliments to create new products, to modify existing products or more generally to understand the mechanisms of perception. Temporal dominance of sensations is a technique to measure temporal perception which consists in choosing sequentially attributes describing a food product over tasting. This work introduces new statistical models based on finite mixtures of semi-Markov chains to describe data collected with the temporal dominance of sensations protocol, allowing different temporal perceptions for a same product within a population. The identifiability of the parameters of such mixtur…

futureStatistics and ProbabilityFOS: Computer and information sciencesGamma distributionmiceComputer sciencemedia_common.quotation_subjectPopulationdominancecomputer.software_genreStatistics - Applications01 natural sciencesMethodology (stat.ME)modelsExpectation-maximization algorithmModel-based clustering010104 statistics & probability0404 agricultural biotechnology[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Bayesian information criterionPerceptionExpectation–maximization algorithmApplications (stat.AP)Temporal dominance of sensations[MATH]Mathematics [math]0101 mathematicseducationStatistics - Methodologymedia_common2. Zero hungereducation.field_of_studyMarkov chainMarkov renewal processStatistical model04 agricultural and veterinary sciencesidentifiabilityMixture modelBayesian information criterion040401 food science[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]IdentifiabilityPenalized likelihoodData miningStatistics Probability and UncertaintycomputertdsCategorical time seriessensations
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CHOOSING OF OPTIMAL REFERENCE SAMPLES FOR BOREAL LAKE CHLOROPHYLL A CONCENTRATION MODELING USING AERIAL HYPERSPECTRAL DATA

2018

Abstract. Optical remote sensing has potential to overcome the limitations of point estimations of lake water quality by providing spatial and temporal information. In open ocean waters the optical properties are dominated by phytoplankton density, while the relationship between color and the constituents is more complicated in inland waters varying regionally and seasonally. Concerning the difficulties relating to comprehensive modeling of complex inland and coastal waters, the alternative approach is considered in this paper: the raw digital numbers (DN) recorded using aerial remote hyperspectral sensing are used without corrections and derived by means of regression modeling to predict C…

lcsh:Applied optics. Photonics010504 meteorology & atmospheric scienceshyperspectral imagingwater quality monitoringchlorophyll a0211 other engineering and technologies02 engineering and technologylcsh:Technology01 natural sciencesStandard deviationPhytoplanktonPredictabilityCluster analysis021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinglcsh:Tlcsh:TA1501-1820Hyperspectral imagingSampling (statistics)Statistical modelRegression analysislake water coloraerial remote sensinglcsh:TA1-2040Environmental sciencelcsh:Engineering (General). Civil engineering (General)The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Statistical Advances in Epidemiology and Public Health

2021

The key role of statistical modeling in epidemiology and public health is unquestionable [...]

medicine.medical_specialtyModels StatisticalManagement scienceHealth Toxicology and MutagenesisPublic healthlcsh:RPublic Health Environmental and Occupational HealthMEDLINElcsh:MedicineStatistical modelStatisticalEditorialn/aEpidemiologyKey (cryptography)medicinePublic HealthSociologyPublic Health.Introductory Journal ArticleModelInternational Journal of Environmental Research and Public Health
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An Emulator Toolbox to Approximate Radiative Transfer Models with Statistical Learning

2015

Physically-based radiative transfer models (RTMs) help in understanding the processes occurring on the Earth’s surface and their interactions with vegetation and atmosphere. When it comes to studying vegetation properties, RTMs allows us to study light interception by plant canopies and are used in the retrieval of biophysical variables through model inversion. However, advanced RTMs can take a long computational time, which makes them unfeasible in many real applications. To overcome this problem, it has been proposed to substitute RTMs through so-called emulators. Emulators are statistical models that approximate the functioning of RTMs. Emulators are advantageous in real practice because…

multi-outputComputer scienceradiative transfer modelsScienceExtrapolationemulatorMachine learningcomputer.software_genreemulator; machine learning; radiative transfer models; multi-output; ARTMO; GUI toolbox; FLEX; fluorescenceAtmosphereARTMOPartial least squares regressionRadiative transferMATLABcomputer.programming_languageArtificial neural networkbusiness.industryQStatistical modelVegetationToolboxFLEXmachine learningPrincipal component analysisGeneral Earth and Planetary SciencesfluorescenceArtificial intelligencebusinessAlgorithmcomputerGUI toolboxRemote Sensing
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