Search results for "Stochastic differential equation"

showing 10 items of 80 documents

Stochastic models for phytoplankton dynamics in Mediterranean Sea

2016

Abstract In this paper, we review some results obtained from three one-dimensional stochastic models, which were used to analyze picophytoplankton dynamics in two sites of the Mediterranean Sea. Firstly, we present a stochastic advection–reaction–diffusion model to describe the vertical spatial distribution of picoeukaryotes in a site of the Sicily Channel. The second model, which is an extended version of the first one, is used to obtain the vertical stationary profiles of two groups of picophytoplankton, i.e. Pelagophytes and Prochlorococcus, in the same marine site as in the previous case. Here, we include intraspecific competition of picophytoplanktonic groups for limiting factors, i.e.…

0106 biological sciences010504 meteorology & atmospheric sciencesStochastic modellingRandom processeAtmospheric sciences01 natural sciencesDeep chlorophyll maximum; Marine ecosystems; Phytoplankton dynamics; Random processes; Spatial ecology; Stochastic differential equations; Ecology Evolution Behavior and Systematics; Ecological ModelingStochastic differential equationMediterranean seaMarine ecosystemSpatial ecology14. Life underwaterPhytoplankton dynamicEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesDeep chlorophyll maximumStochastic differential equationbiologyStochastic processEcology010604 marine biology & hydrobiologyEcological Modelingbiology.organism_classificationEcology Evolution Behavior and SystematicSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Light intensitySpatial ecologyDeep chlorophyll maximumProchlorococcusEcological Complexity
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Crowd-Averse Robust Mean-Field Games: Approximation via State Space Extension

2016

We consider a population of dynamic agents, also referred to as players. The state of each player evolves according to a linear stochastic differential equation driven by a Brownian motion and under the influence of a control and an adversarial disturbance. Every player minimizes a cost functional which involves quadratic terms on state and control plus a cross-coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term “crowd-averse.” Motivations for this model are analyzed and discussed in three main contexts: a stock market application, a production engineering example, and a dynamic demand management problem in power systems. For th…

0209 industrial biotechnologyStochastic stabilityMathematical optimizationCollective behaviorTechnologyComputer sciencePopulationcontrol designcrowd-averse robust mean-field games state space extension dynamic agents linear stochastic differential equation Brownian motion adversarial disturbance cost functional cross-coupling mean-field term collective behavior stock market application production engineering example dynamic demand management problem robust mean-field game approximation error stochastic stability microscopic dynamics macroscopic dynamicscontrol engineering02 engineering and technology01 natural sciencesStochastic differential equationoptimal control020901 industrial engineering & automationQuadratic equationAutomation & Control SystemsEngineeringClosed loop systemsSettore ING-INF/04 - AutomaticaApproximation errorRobustness (computer science)Control theory0102 Applied MathematicsState space0101 mathematicsElectrical and Electronic EngineeringeducationBrownian motioneducation.field_of_studyScience & TechnologyStochastic process010102 general mathematicsRelaxation (iterative method)Engineering Electrical & ElectronicOptimal controlComputer Science Applications0906 Electrical and Electronic EngineeringIndustrial Engineering & AutomationMean field theoryControl and Systems EngineeringSettore MAT/09 - Ricerca Operativa0913 Mechanical Engineering
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Stochastic differential calculus for wind-exposed structures with autoregressive continuous (ARC) filters

2008

In this paper, an alternative method to represent Gaussian stationary processes describing wind velocity fluctuations is introduced. The technique may be considered the extension to a time continuous description of the well-known discrete-time autoregressive model to generate Gaussian processes. Digital simulation of Gaussian random processes with assigned auto-correlation function is provided by means of a stochastic differential equation with time delayed terms forced by Gaussian white noise. Solution of the differential equation is a specific sample of the target Gaussian wind process, and in this paper it describes a digitally obtained record of the wind turbolence. The representation o…

Autoregressive continuous (ARC) modelRenewable Energy Sustainability and the EnvironmentStochastic processMechanical EngineeringGaussianOrnstein–Uhlenbeck processGaussian random fieldStochastic differential equationsymbols.namesakeQuasi-static theoryAutoregressive modelFourier transformsymbolsGaussian functionCalculusStochastic differential calculuApplied mathematicsGaussian random processeSettore ICAR/08 - Scienza Delle CostruzioniGaussian processCivil and Structural EngineeringMathematicsJournal of Wind Engineering and Industrial Aerodynamics
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Quadratic backward stochastic differential equations

2017

Tässä tutkielmassa analysoimme takaperoisia stokastisia differentiaaliyhtälöitä. Aloitamme esittelemällä stokastiset prosessit, Brownin liikkeen, stokastiset integraalit ja Itôn kaavan. Tämän jälkeen siirrymme tarkastelemaan stokastisia differentiaaliyhtälöitä ja lopulta takaperoisia stokastisia differentiaaliyhtälöitä. Tämän tutkielman pääaiheena on takaperoiset stokastiset differentiaaliyhtälöt kvadraattisilla oletuksilla. Näillä oletuksilla todistamme olemassaoloteoreeman ja tietyt säännöllisyysehdot takaperoisen stokastisen differentiaaliyhtälön ratkaisulle. In this thesis, we analyze backward stochastic differential equations. We begin by introducing stochastic processes, Brownian moti…

Backward Stochastic Differential EquationsStochastics
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How diffusivity, thermocline and incident light intensity modulate the dynamics of Deep Chlorophyll Maximum in Tyrrhenian Sea

2015

During the last few years theoretical works have shed new light and proposed new hypotheses on the mechanisms which regulate the spatio-temporal behaviour of phytoplankton communities in marine pelagic ecosystems. Despite this, relevant physical and biological issues, such as effects of the time- dependent mixing in the upper layer, competition between groups, and dynamics of non-stationary deep chlorophyll maxima, are still open questions. In this work, we analyze the spatio-temporal behaviour of five phytoplankton populations in a real marine ecosystem by using a one-dimensional reaction-diffusion-taxis model. The study is performed, taking into account the seasonal variations of environm…

Chlorophyll0106 biological sciencesLight010504 meteorology & atmospheric sciencesMixed layerlcsh:MedicineOceanographyRandom processeAtmospheric sciences01 natural scienceschemistry.chemical_compoundPhytoplanktonMediterranean SeaMarine ecosystemSpatial ecologySeawaterMarine ecosystem14. Life underwaterPhytoplankton dynamiclcsh:Science0105 earth and related environmental sciencesDeep chlorophyll maximumMultidisciplinaryEcology010604 marine biology & hydrobiologylcsh:RTemperaturePelagic zoneModels TheoreticalSpatial ecology; Marine ecosystems; Phytoplankton dynamics; Deep chlorophyll maximum; Random processes; Stochastic differential equationsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Light intensitychemistry13. Climate actionChlorophyllPhytoplanktonStochastic differential equationsDeep chlorophyll maximumEnvironmental sciencelcsh:QThermoclineAlgorithmsResearch Article
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Dynamics of Two Picophytoplankton Groups in Mediterranean Sea: Analysis of the Deep Chlorophyll Maximum by a Stochastic Advection-Reaction-Diffusion …

2013

A stochastic advection-reaction-diffusion model with terms of multiplicative white Gaussian noise, valid for weakly mixed waters, is studied to obtain the vertical stationary spatial distributions of two groups of picophytoplankton, i.e., picoeukaryotes and Prochlorococcus, which account about for 60% of total chlorophyll on average in Mediterranean Sea. By numerically solving the equations of the model, we analyze the one-dimensional spatio-temporal dynamics of the total picophytoplankton biomass and nutrient concentration along the water column at different depths. In particular, we integrate the equations over a time interval long enough, obtaining the steady spatial distributions for th…

ChlorophyllPopulation DynamicsPopulation ModelingRandom processeAtmospheric scienceschemistry.chemical_compoundTheoretical EcologyWater columnMediterranean seaDeep chlorophyll maximumCalculusMultidisciplinaryEcologybiologyEcologyApplied MathematicsPhysicsQStatisticsRComplex SystemsStochastic differential equationsInterdisciplinary PhysicsMedicineDeep chlorophyll maximumProchlorococcusResearch ArticleChlorophyll aScienceStatistical MechanicsDifferential EquationsPhytoplanktonMarine ecosystemMediterranean SeaSpatial ecologyStatistical MethodsPhytoplankton dynamicBiologyComputerized SimulationsStochastic ProcessesPopulation BiologyAdvectionComputational BiologyRandom VariablesModels TheoreticalSpatial ecology; Marine ecosystems; Phytoplankton dynamics; Deep chlorophyll maximum; Random processes; Stochastic differential equationsProbability Theorybiology.organism_classificationMarine EnvironmentsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Nonlinear DynamicschemistryChlorophyllComputer SciencePhytoplanktonEcosystem ModelingMathematicsEcological EnvironmentsPLoS ONE
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Existence, uniqueness and comparison results for BSDEs with Lévy jumps in an extended monotonic generator setting

2018

We show existence of a unique solution and a comparison theorem for a one-dimensional backward stochastic differential equation with jumps that emerge from a L\'evy process. The considered generators obey a time-dependent extended monotonicity condition in the y-variable and have linear time-dependent growth. Within this setting, the results generalize those of Royer (2006), Yin and Mao (2008) and, in the $L^2$-case with linear growth, those of Kruse and Popier (2016). Moreover, we introduce an approximation technique: Given a BSDE driven by Brownian motion and Poisson random measure, we consider BSDEs where the Poisson random measure admits only jumps of size larger than $1/n$. We show con…

Comparison theorembackward stochastic differential equationMonotonic function01 natural sciencesLévy processlcsh:QA75.5-76.95010104 statistics & probabilityMathematics::ProbabilityApplied mathematicsUniqueness0101 mathematicsBrownian motionstokastiset prosessitMathematicsLévy processResearch010102 general mathematicsComparison resultsPoisson random measureBackward stochastic differential equationlcsh:Electronic computers. Computer science60H10lcsh:Probabilities. Mathematical statisticscomparison theoremlcsh:QA273-280differentiaaliyhtälötMathematics - ProbabilityGenerator (mathematics)existence and uniquenessProbability, Uncertainty and Quantitative Risk
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Dynamics of two competing species in the presence of Lévy noise sources

2010

We consider a Lotka-Volterra system of two competing species subject to multiplicative alpha-stable Lévy noise. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence both of a periodic driving term and an additive alpha-stable Lévy noise. We study the species dynamics, which is characterized by two different regimes, exclusion of one species and coexistence of both. We find quasi-periodic oscillations and stochastic resonance phenomenon in the dynamics of the competing species, analysing the role of the Lévy noise sources.

Competitive BehaviorComplex systemsBistabilityStochastic resonancePopulation DynamicsComplex systemModels BiologicalStochastic differential equationControl theoryQuantitative Biology::Populations and EvolutionAnimalsHumansComputer SimulationStatistical physicsEcosystemMathematicsPopulation dynamics and ecological pattern formationModels StatisticalStochastic processDynamics (mechanics)Multiplicative functionStochastic analysis methods (Fokker-Planck Langevin etc.)Adaptation PhysiologicalRandom walks and Lévy flightQuasiperiodic functionPredatory Behavior
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The interrelation between stochastic differential inclusions and set-valued stochastic differential equations

2013

Abstract In this paper we connect the well established theory of stochastic differential inclusions with a new theory of set-valued stochastic differential equations. Solutions to the latter equations are understood as continuous mappings taking on their values in the hyperspace of nonempty, bounded, convex and closed subsets of the space L 2 consisting of square integrable random vectors. We show that for the solution X to a set-valued stochastic differential equation corresponding to a stochastic differential inclusion, there exists a solution x for this inclusion that is a ‖ ⋅ ‖ L 2 -continuous selection of X . This result enables us to draw inferences about the reachable sets of solutio…

Continuous-time stochastic processApplied MathematicsMathematical analysisStochastic calculusMalliavin calculusStochastic partial differential equationsymbols.namesakeStochastic differential equationDifferential inclusionRunge–Kutta methodsymbolsApplied mathematicsAnalysisMathematicsAlgebraic differential equationJournal of Mathematical Analysis and Applications
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The Master Equation

2009

Continuous-time stochastic processsymbols.namesakeStochastic differential equationQuantum stochastic calculusStochastic processMaster equationKinetic schemesymbolsStatistical physicsChapman–Kolmogorov equationMathematics
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