Dissertations / Theses on the topic 'Modèle dynamique stochastiques'
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Personne, Arnaud. "Dynamique du modèle de Moran en environnement aléatoire." Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC102.
Full textIn some ecosystems and more particularly in virgin tropical forests, different species having the same ecological requirements coexist in the same environment. For example, some forests have over a hundred different tree species on one hectare. To explain this incrediblediversity, scientists have built models in which the community composition isonly due to the stochastic dispersion of individuals.The mathematical model studied in this thesis follows this line. It was suggested by Mr. Kalyuzhni in an article where he justifies its relevance. It is known as the Moran model in random environment. It is therefore a question of studying a birth and death process taking into account the environmental stochasticity (climates, diseases, etc.) To study this dynamic, we use an approximation by a diffusion, on the classical scale where the acceleration in time is given by the square of the population size, moreover selective advantage and immigration are inversely proportional to thethis size. The selective advantage varies randomly and is modeled by a Markov jump process. We study the convergence in law of the processes sequence and give a quantitative estimate of the error made for a given population. We are then interested in the moments estimation of the population frequencies, motivated in particular by biodiversity indices such as the Simpson's index andbased on the approximations obtained before.In the case of a non-zero selection, the stochastic differential equation governing a moment appeals to the higher order moment. To overcome this difficulty, we create a closure method to reduce the study of the first moments to a finite system of differential equations. We give an estimation of the error made by neglecting the terms of higher degrees. Finally, in the case of two species and with constant coefficients, we give an estimate of the convergence speed of the diffusion towards the stationary measure. In a second time, we are interested in a time scale proportional to the size of the population. This leads to a convergence of the process law towards a deterministic limitcharacterized by an ordinary differential equation. The selection coefficient evolving randomly, still following a Markov jump process, this process is a PDMP.We then study the persistence of the different species and the potential coexistencethanks the persistence theory, developed by Benaïm and Schreiber. In this part, we are particularly interested in the case where all the species persist. With only two environments: we show that two species can persist but not three. With more environments,the explicit classification stay an open problem but an example of persistence with three speciesand three environments is given
Arnst, Maarten. "Inversion of probabilistic models of structures using measured transfer functions." Châtenay-Malabry, Ecole centrale de Paris, 2007. http://www.theses.fr/2007ECAP1037.
Full textThe aim of this thesis is to develop a methodology for the experimental identification of probabilistic models for the dynamical behaviour of structures. The inversion of probabilistic structural models with minimal parameterization, introduced by Soize, from measured transfer functions is in particular considered. It is first shown that the classical methods of estimation from the theory of mathematical statistics, such as the method of maximum likelihood, are not well-adapted to formulate and solve this inverse problem. In particular, numerical difficulties and conceptual problems due to model misspecification are shown to prohibit the application of the classical methods. The inversion of probabilistic structural models is then formulated alternatively as the minimization, with respect to the parameters to be identified, of an objective function measuring a distance between the experimental data and the probabilistic model. Two principles of construction for the definition of this distance are proposed, based on either the loglikelihood function, or the relative entropy. The limitation of the distance to low-order marginal laws is demonstrated to allow to circumvent the aforementioned difficulties. The methodology is applied to examples featuring simulated data and to a civil and environmental engineering case history featuring real experimental data
Guerineau, Lise. "Analyse statistique de modèles de fiabilité en environnement dynamique." Lorient, 2013. http://www.theses.fr/2013LORIS297.
Full textWe propose models which integrate time varying stresses for assessing reliability of the electrical network. Our approach is based on the network observation and consists of statistical and probabilistic modelling of failure occurrence. The great flexibility allowed by the piecewise exponential distribution makes it appropriate to model time-to-failure of a component under varying environmental conditions. We study properties of this distribution and make statistical inference for different observation schemes. Models relating components reliability with environmental constraints, and relying on the piecewise exponential distribution, are proposed. The maximum likelihood is assessed on both simulated and real data sets. Then, we consider a multi-component system whose evolution is linked with the corrective maintenance performed. Reliability of this system can be described using stochastic processes. We present inference methods according to the nature of the observation. Discrete observation can be formulated in terms of missing data; the EM algorithm is used to reach estimates in this situation. Stochastic versions of this algorithm have been considered to overcome a possible combinatorial explosion preventing from the EM algorithm implementation. Numerical examples are presented for the proposed algorithms
Batou, Anas. "Identification des forces stochastiques appliquées à un système dynamique non linéaire en utilisant un modèle numérique incertain et des réponses expérimentales." Phd thesis, Université Paris-Est, 2008. http://tel.archives-ouvertes.fr/tel-00472080.
Full textGruet, Pierre. "Quelques problèmes d'estimation et de contrôle optimal pour les processus stochastiques dans un cadre de modélisation des prix des marchés de l'électricité." Sorbonne Paris Cité, 2015. https://theses.hal.science/tel-01238618.
Full textIn this thesis, we study mathematical models for the representation of prices on the electricity markets, from the viewpoints of statistics of random processes and optimal stochastic control. In a first part, we perform estimation of the components of the volatility coefficient of a multidimensional diffusion process, which represents the evolution of prices in the electricity forward market. It is driven by two Brownian motions. We aim at achieving estimation efficiently in terms of convergence rate and, concerning the parametric part of those components, in terms of limit law. To do so, we must extend the usual notion of efficiency in the Cramér-Rao sense. Our estimation methods are based on realized quadratic variation of the observed process. In a second part, we add model error terms to the previous model, in order to tare for some kind of degeneration occurring in it as soon as the dimension of the observed process is greater than two. Our estimation methods are still based on realized quadratic variation, and we give other tools in order to keep on estimating the volatility components with the optimal rate when error terms are present. Then, numerical tests provide us with some evidence that such errors are present in the data. Finally, we solve the problem of a producer, which trades on the electricity intraday market in order to tope with the uncertainties on the outputs of his production units. We assume that there is market impact, so that the producer influences prices as he trades. The price and the forecast of the consumers' demand are modelled by jump diffusions. We use the tools of optimal stochastic control to determine the strategy of the producer in an approximate problem. We give conditions so that this strategy is close to optimality in the original problem, as well as numerical illustrations of that strategy
Barré, Chloé. "Physique statistique des phénomènes de blocage dans les flux particulaires." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066227/document.
Full textThis manuscript presents a study of blocking phenomenon in particulate streams flowing through anarrow channel. In particular, it examines situations in which blocking is controlled by the limitedcarrying capacity of the channel. It builds on a simple stochastic model, introduced by Gabrielli etal. (Phys. Rev. Lett. 110, 170601, 2013), in which particles arrive randomly according to a Poissondistribution at the entrance of a one-dimensional channel with an intensity λ and, unless interrupted,exit after a transit time, τ. Blocking occurs instantaneously when N=2 particles are simultaneouslypresent in the channel. The quantities of interest include the probability that the channel is still openat time t (survival probability) and the flux and total number of exiting particles. The thesisexamines a number of generalizations including when more than two particles must be present toinduce blockage, N>2, a time dependent intensity, a finite blocking time, and multi-channelsystems. We obtain exact and approximate analytical results using tools such as the masterequations describing the evolution of the n-particle partial probabilities, large deviation theory andqueuing theory. The theoretical results are validated by comparison with the results of numericalsimulations. The final chapter of the thesis uses a different approach, namely a brownian dynamics simulation of a two dimensional system of soft particles subjected to an external driving and dragforces. The presence of an obstacle in the middle of the channel can cause irreversible orintermittent clogging depending on the system geometry, temperature and particle stiffness
Naso, Aurore. "Intermittence en Turbulence pleinement développée et en Dynamique non linéaire." Phd thesis, Université de Nice Sophia-Antipolis, 2005. http://tel.archives-ouvertes.fr/tel-00011134.
Full textLa seconde partie est consacrée à l'étude de la transition au chaos spatio-temporel par intermittence dans un système hydrodynamique réel. Cette transition est d'abord étudiée quantitativement, puis un modèle d'intermittence spatio-temporelle est appliqué aux conditions aux limites de l'expérience. Comme le système réel, les solutions de ce modèle présentent pour certaines valeurs des paramètres dont il dépend un régime de bistabilité, près du seuil, entre l'intermittence spatio-temporelle et un régime où le désordre n'est présent que sur les bords.
Gajda, Dorota. "Optimisation des méthodes algorithmiques en inférence bayésienne. Modélisation dynamique de la transmission d'une infection au sein d'une population hétérogène." Phd thesis, Université Paris Sud - Paris XI, 2011. http://tel.archives-ouvertes.fr/tel-00659618.
Full textFavelier, Thomas. "Couplage de la vélocimétrie par images de particules en deux temps avec la décomposition en modes propres pour la caractérisation d'un écoulement." Phd thesis, Université Claude Bernard - Lyon I, 2006. http://tel.archives-ouvertes.fr/tel-00080473.
Full textUne étude expérimentale de l'écoulement bidimensionnel en moyenne en aval d'un cylindre semi-circulaire, par vélocimétrie par image de particules en deux temps (PIV2T) caractérise l'écoulement
Une analyse POD du champ de vitesse permet d'extraire les modes spatiaux et de définir un paramètre de phase décrivant l'instationnarité à grande échelle qui régit la partie déterministe. La modélisation de l'évolution temporelle des coefficients associés aux modes s'effectue par des fonctions soit harmoniques pour la partie déterministe, soit stochastiques pour la partie aléatoire.
La modélisation est en accord avec les mesures expérimentales des premiers moments statistiques en un point et des fonctions de corrélation spatio-temporelle du champ de vitesse.
Zaatour, Riadh. "Propriétés empiriques et modélisation d’actifs en haute fréquence." Thesis, Châtenay-Malabry, Ecole centrale de Paris, 2013. http://www.theses.fr/2014ECAP0027/document.
Full textThis thesis explores theoretical and empirical aspects of price formation and evolution at high frequency. We begin with the study of the joint dynamics of an option and its underlying. The high frequency data making observable the realized volatility process of the underlying, we want to know if this information is used to price options. We find that the market does not process this information to fix option prices. The stochastic volatility models are then to be considered as reduced form models. Nevertheless, this study tests the relevance of an empirical hedging parameter that we call effective delta. This is the slope of the regression of option price increments on those of the underlying. It proves to be a satisfactory model-independent hedging parameter. For the price dynamics, we turn our attention in the following chapters to more explicit models of market microstructure. One of the characteristics of the market activity is its clustering. Hawkes processes are point processes with this characteristic, therefore providing an adequate mathematical framework for the study of this activity. Moreover, the Markov property associated to these processes when the kernel is exponential allows to use powerful analytical tools such as the infinitesimal generator and the Dynkin formula to calculate various quantities related to them, such as moments or autocovariances of the number of events on a given interval. We begin with a monovariate framework, simple enough to illustrate the method, but rich enough to enable applications such as the clustering of arrival times of market orders, prediction of future market activity knowing past activity, or characterization of unusual shapes, but nevertheless observed, of signature plot, where the measured volatility decreases when the sampling frequency increases. Our calculations also allow us to make instantaneous calibration of the process by relying on the method of moments. The generalization to the multidimensional case then allow us to capture, besides the clustering, the phenomenon of mean reversion, which also characterizes the market activity observed in high frequency. General formulas for the signature plot are then obtained and used to connect its shape to the relative importance of clustering or mean reversion. Our calculations also allow to obtain the explicit form of the volatility associated with the diffusive limit, therefore connecting the dynamics at microscopic level to the macroscopic volatility, for example on a daily scale. Additionally, modelling buy and sell activity by Hawkes processes allows to calculate the market impact of a meta order on the asset price. We retrieve and explain the usual concave form of this impact as well as its relaxation with time. The analytical results obtained in the multivariate case provide the adequate framework for the study of the correlation. We then present generic results on the Epps effect as well as on the formation of the correlation and the lead lag
Fillon, Romain. "Incertitudes climatiques." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASI014.
Full textI study climate uncertainties and their economic impacts. In the first chapter, we discuss the limitations and alternatives to the standard criteria for intertemporal social choice. While these criteria are well-suited for standard risks, their use should be reconsidered in the presence of irreversible regime-shift risks, such as climate tipping points, where the aggregate risk to the welfare of present and future generations is significant. Indeed, these models assume that the planner is risk-neutral regarding this aggregate risk. In contrast, we show that introducing risk aversion over time significantly increases the social cost of carbon (SCC) in the presence of irreversible catastrophic tipping-point risks. In the second chapter, we decompose the climate module of economic models to analyze and quantify how the dynamic interactions between global climate risk and climate subsystems affect global climate policy and the regional management of these subsystems. We apply our theoretical framework to the controversial fate of the Amazon rainforest. Our approach yields two key methodological insights. First, the SCC should include the impact that a marginal increase in cumulative global emissions has on the dynamics of the Amazon rain-forest. This includes scaling current policies to account for carbon emissions from the Amazon under a changing climate, as well as an insurance channel—the "Amazonian beta"—as the social value of carbon emissions varies according to the states of the world in which they occur. Second, the social value of the Amazon rainforest as a carbon stock cannot be reduced to the quantity of carbon it contains; the social cost of the dynamic system is also crucial, that is, the cost of a marginal decline in the state of the subsys-tem that reduces its capacity to persist. In the third chapter, we quantify the extent to which the spatial and temporal aggregation of temperature data in climate impact projections might obscure scientific uncertainties between climate projections and underestimate future climate damages. In the fourth chapter, I quantify the impact of biophysical channels (albedo, evapotranspiration, roughness) on the distribution and aggregate impacts of climate change on welfare along the Shared Concentration Pathway SSP2-4.5 at a global scale and at 1° resolution. These channels are endogenous to regional economic activities due to land-use changes from agriculture and urbanization, and they interact with adaptation strategies such as migration or structural change. Thus, my dissertation follows three directions: documenting the economic consequences of climate uncertainties, contributing methodologically to the study of uncertainty at the interface of human and natural systems, and enriching the literature on intertemporal normative social choice through numerical models used for quantification
Winant, Pablo. "Modèles stochastiques d'équilibre général dynamique à deux agents." Paris, EHESS, 2014. http://www.theses.fr/2014EHES0048.
Full textThis dissertation focuses on the numerical solution and properties of dynamic general equilibrium models, in which two agents can trade in one or many assets. In the first chapter, I develop an approximation method around a « risky steady-state » which captures precautionary behavior of economic agents. In a simple two-countries models, I show that this effect stabilizes the net foreign asset position. The second chapter provides theoretical foundations to adapt classical perturbation methods in order to characterize dynamic portfolios in general or partial equilibrium. It also evaluates its precision relative to other concurring methods. The third chapter studies financial integration in the stochastic neoclassical model. By comparing quantitatively the effects of precautionary savings by risky countries with the effects of efficient capital allocation, the model is able to predict capital flow reversals a few years after integration. Counter-intuitively, the safer country benefits more from financial integration that the risky one. Last chapters links an increase in income inequalities with a debt accumulation by the 95% poorest households. The debt buildup induces in turn a rational default by bottom earners, leading to crises episodes similar to the great depression and the great recession. The debt accumulation comes from the preference for wealth by top earners that matches the observed behavior of the top 5% households. When calibrated to empirical data, the model is able to reproduce the magnitude of debt accumulation and the increase in crisis probability that were historically observed before the two historical episodes
Baili, Hana. "Caractérisation statistique de mesures dynamiques continues à partir d'un modèle de connaissance." Paris 11, 2002. http://www.theses.fr/2002PA112077.
Full textIn this thesis, we deal with statistical characterization of dynamical continuous measurements within a knowledge-based model. A measurement is any quantity to be observed within a system; we talk about indirect measurement when this quantity cannot be directly given by some sensors. The term dynamic refers to the evolution of the measurement in time. The model is said knowledge-based because it comes from the mathematical traduction of the system physics, as opposed to black-box models. The quantities that when fixed, cause the others to be determined uniquely, are called model's data, such as initial conditions, observations, controls, etc. Often, some of them are unknown because they are random or deterministic but the model comes from an incomplete description of the system. A prior information about some uncertainty can be acquired; it will consist of its average and dispersion, if it is random, or of some set that specifies its values, if it is deterministic. Given the model described below, what's about the measurement? We propose here a probabilistic approach to characterize the measurement; in fact the modelling step, involved at the beginning, consists in transforming the model into a stochastic differential equation (sde) determining a process such that estimating the probability density function (pdf) of this process achieves the ultimate measurement; this is the "statistical characterization". Chapter 3 describes the modelization task in general, using McShane's stochastic calculus as theoretical basis. Chapters 4, 5, and 6 present our methods for estimating the pdf of the (extended) measurement
Nguyen, Thanh Thien. "Géométrie de systèmes dynamiques stochastiques et modèles de second ordre pour les marchés financiers." Toulouse 3, 2014. http://thesesups.ups-tlse.fr/2481/.
Full textThis thesis is devoted to a study of qualitative geometrical properties of stochastic dynamical systems, namely their symmetries, reduction and integrability, with applications to the problem of modelling of financial markets. It consists of four chapters. Chapter 1 is a brief review of basic notions from the theory of stochastic dynamical systems (SDS for short) written in Stratonovich form, and also Hamiltonian systems. The material in this chapter is not new, and is included in this thesis to make it self-contained. In Chapter 2, we study the problem of reduction of SDS with respect to a proper action of a Lie group. This is an important problem in the theory of dynamical systems in general. Various famous processes in stochastic calculus, e. G. The Bessel process, can be viewed as a result of reduction. But there are still some relatively simple results that we did not find in the literature and so we wrote them down in Chapter 2. In particular, we proved that if a SDS is not invariant but only diffusion-wise invariant with respect to a group action, then we can still do reduction. We also give necessary and sufficient conditions for a SDS to be reductible (i. E. Projectable) with respect to a given submersion map. In Chapter 3, we introduce and study the notion of integrability of SDS. This integrability notion lies between the integrability notion for classical deterministic systems and the integrability notion for quantum dynamical systems. One of the most fundamental results in the theory of classical integrable deterministic dynamical systems is the existence of so called Liouville torus actions which have the structure-preserving property. Those Liouville torus actions imply the quasi-periodic behaviour of proper integrable systems, allow one to do averaging and reduction (also for perturbations of integrable systems), find action-angle variables, and do quantization. We extend this fundamental result about the existence of structure-preserving Liouville torus actions to the case of integrable SDS. We also show how integrable SDS are naturally related to the problem of Riemannian metrics with integrable geodesic flows, which is a very interesting problem in geometry with many recent results in the literature. In Chapter 4, we argue that first order (stochastic differential) models of the stock markets, e. G. The famous Black-Scholes model, is conceptually not correct for the description of what is happening in the financial markets, even though they can be used for pricing financial derivative products. More realistic models of the market must be of second order, i. E. Taking into account both the price variables and the momentum variables. We develope in this chapter two simple second order models, namely the stochastic oscillator and the stochastic constrained n-oscillator, which can explain a lot of phenomena in the markets. A key notion introduced in these models is speculation energy (in analogy with physical energy), and we claim that it is this speculation energy which moves the financial markets
Hellio, Gabrielle. "Modèles stochastiques de mesures archéomagnétiques." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAU004/document.
Full textThe aim of this thesis is to build stochastic models of the magnetic field for the last four millenia from archeomagnetic measurements. The sparse repartition of these data in space and time, and their associated large measurement and dating errors lead to an ill-posed problem. To determine the best solution, one needs to choose some prior information which consists usually on arbitrary regularizations in space and time. Instead, we use the temporal statistics of the geomagnetic field available from satellites, observatories and paleomagnetic measurements, and validated by numerical simulations, to define our prior information via auto-covariance functions. This bayesian method allows to get rid of arbitrary support functions, like splines, usually necessary to interpolate the model in time. The result consists in an ensemble of several possible realizations of the magnetic field. The ensemble dispersion represents the model uncertainties. We find that the methodology can be adapted to account for the age uncertainties and we use Markov Chain Monte Carlo to explore the possible dates of observations. This method improves the bootstrap method which gives the same weight to every draws of dates presenting very disparate probabilities. Each ensemble of realizations is then constructed from each selected model and the result is presented as a probability density function. The bayesian method together with the Markov Chain Monte Carlo provides regional time series with rapid variations compared to previous studies. We find that the possible values of geomagnetic field elements are not necessarily normally distributed. Another output of the model is better age estimates of archeological artefacts. The bayesian method has been used to build global models for which the axial dipole presents more rapid variations than for previous studies. Moreover, the obtained magnetic field displays reasonably similar behavior than models obtained from direct measurements (satellites, observatories, historical), despite very few data and sparser repartition. Models obtained from this study offer an alternative to published regularized models and can be used in a purpose of data assimilation together with dynamical models in the Earth's core
Laslier, Benoît. "Dynamique stochastique d'interface discrète et modèles de dimères." Phd thesis, Université Claude Bernard - Lyon I, 2014. http://tel.archives-ouvertes.fr/tel-01044463.
Full textLaslier, Benoît. "Dynamique stochastique d’interface discrète et modèles de dimères." Thesis, Lyon 1, 2014. http://www.theses.fr/2014LYO10110/document.
Full textWe studied the Glauber dynamics on tilings of finite regions of the plane by lozenges or 2 × 1 dominoes. These tilings are naturally associated with surfaces of R^3, which can be seen as interfaces in statistical physics models. In particular, lozenge tilings correspond to three dimensional Ising model at zero temperature. More precisely, tilings of a finite regions are in bijection with Ising configurations with some boundary conditions (depending on the tiled domain). These boundary conditions impose the coexistence of the + and - phases, together with the position of the boundary of the interface. In the thermodynamic limit where L, the characteristic length of the system, tends toward infinity, these interface follow a law of large number and converge to a deterministic limit shape depending only on the boundary condition. When the limit shape is planar and for lozenge tilings, Caputo, Martinelli and Toninelli [CMT12] showed that the mixing time of the dynamics is of order (L^{2+o(1)}) (diffusive scaling). We generalized this result to domino tilings, always in the case of a planar limit shape. We also proved a lower bound Tmix ≥ cL^2 which improve on the result of [CMT12] by a log factor. When the limit shape is not planar, it can either be analytic or have some “frozen” domains where it is degenerated in a sense. When it does not have such frozen region, and for lozenge tilings, we showed that the Glauber dynamics becomes “macroscopically close” to equilibrium in a time L^{2+o(1)}
De, Larrard Adrien. "Dynamique de carnets d'ordres boursiers : modèles stochastiques et théorèmes limites." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2012. http://tel.archives-ouvertes.fr/tel-00738647.
Full textLenormand, Maxime. "Initialiser et calibrer un modèle de microsimulation dynamique stochastique : application au modèle SimVillages." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2012. http://tel.archives-ouvertes.fr/tel-00822114.
Full textTouboul, Jonathan. "Modèles nonlinéaires et stochastiques en neuroscience." Palaiseau, Ecole polytechnique, 2008. http://www.theses.fr/2008EPXX0028.
Full textMendoume, Minko Ignace Davy. "Identification des systèmes dynamiques stochastiques." Phd thesis, Clermont-Ferrand 2, 2005. https://tel.archives-ouvertes.fr/tel-00676619/document.
Full textEzvan, Olivier. "Multilevel model reduction for uncertainty quantification in computational structural dynamics." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1109/document.
Full textThis work deals with an extension of the classical construction of reduced-order models (ROMs) that are obtained through modal analysis in computational linear structural dynamics. It is based on a multilevel projection strategy and devoted to complex structures with uncertainties. Nowadays, it is well recognized that the predictions in structural dynamics over a broad frequency band by using a finite element model must be improved in taking into account the model uncertainties induced by the modeling errors, for which the role increases with the frequency. In such a framework, the nonparametric probabilistic approach of uncertainties is used, which requires the introduction of a ROM. Consequently, these two aspects, frequency-evolution of the uncertainties and reduced-order modeling, lead us to consider the development of a multilevel ROM in computational structural dynamics, which has the capability to adapt the level of uncertainties to each part of the frequency band. In this thesis, we are interested in the dynamical analysis of complex structures in a broad frequency band. By complex structure is intended a structure with complex geometry, constituted of heterogeneous materials and more specifically, characterized by the presence of several structural levels, for instance, a structure that is made up of a stiff main part embedding various flexible sub-parts. For such structures, it is possible having, in addition to the usual global-displacements elastic modes associated with the stiff skeleton, the apparition of numerous local elastic modes, which correspond to predominant vibrations of the flexible sub-parts. For such complex structures, the modal density may substantially increase as soon as low frequencies, leading to high-dimension ROMs with the modal analysis method (with potentially thousands of elastic modes in low frequencies). In addition, such ROMs may suffer from a lack of robustness with respect to uncertainty, because of the presence of the numerous local displacements, which are known to be very sensitive to uncertainties. It should be noted that in contrast to the usual long-wavelength global displacements of the low-frequency (LF) band, the local displacements associated with the structural sub-levels, which can then also appear in the LF band, are characterized by short wavelengths, similarly to high-frequency (HF) displacements. As a result, for the complex structures considered, there is an overlap of the three vibration regimes, LF, MF, and HF, and numerous local elastic modes are intertwined with the usual global elastic modes. This implies two major difficulties, pertaining to uncertainty quantification and to computational efficiency. The objective of this thesis is thus double. First, to provide a multilevel stochastic ROM that is able to take into account the heterogeneous variability introduced by the overlap of the three vibration regimes. Second, to provide a predictive ROM whose dimension is decreased with respect to the classical ROM of the modal analysis method. A general method is presented for the construction of a multilevel ROM, based on three orthogonal reduced-order bases (ROBs) whose displacements are either LF-, MF-, or HF-type displacements (associated with the overlapping LF, MF, and HF vibration regimes). The construction of these ROBs relies on a filtering strategy that is based on the introduction of global shape functions for the kinetic energy (in contrast to the local shape functions of the finite elements). Implementing the nonparametric probabilistic approach in the multilevel ROM allows each type of displacements to be affected by a particular level of uncertainties. The method is applied to a car, for which the multilevel stochastic ROM is identified with respect to experiments, solving a statistical inverse problem. The proposed ROM allows for obtaining a decreased dimension as well as an improved prediction with respect to a classical stochastic ROM
Porcher, Raphaël. "Éstimation d'invariants dynamiques (exposants de Lyapunov) pour des systèmes dynamiques stochastiques." Paris 6, 2002. http://www.theses.fr/2002PA066301.
Full textSlimani, Safia. "Système dynamique stochastique de certains modèles proies-prédateurs et applications." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMR123/document.
Full textThis work is devoted to the study of the dynamics of a predator-prey system of Leslie-Gower type defined by a system of ordinary differential equations (EDO) or stochastic differential equations (EDS), or by coupled systems of EDO or EDS. The main objective is to do mathematical analysis and numerical simulation of the models built. This thesis is divided into two parts : The first part is dedicated to a predator-prey system where the prey uses a refuge, the model is given by a system of ordinary differential equations or stochastic differential equations. The purpose of this part is to study the impact of the refuge as well as the stochastic perturbation on the behavior of the solutions of the system. In the second part, we consider a networked predator-prey system. We show that symmetric couplings speed up the convergence to a stationary distribution
Larrard, Adrien de. "Dynamique de carnets d'ordres boursiers : modeles stochastiques et theoremes limites." Paris 6, 2012. http://www.theses.fr/2012PA066409.
Full textThis thesis proposes a mathematical framework for the modeling the intraday dynamics of prices and order flow in it limit order markets: electronic markets where participants buy and sell a financial contract by submitting market orders and limit orders at high frequency to a centralized it limit order book. We propose a stochastic model of a limit order book as a queueing system representing the dynamics of the queues of buysell limit orders at the best available (bid/ask) price levels and argue that the main features of price dynamics in limit order markets may be understood in this framework. We study in detail the relation between the statistical properties of the price and the dynamics of the point process describing the arrival and execution of orders, first in a Markovian setting (Chapter ref chapter. Markov) then, using asymptotic methods, in a more general setting of a stationary point process in the it heavy traffic limit, where orders arrive very frequently, as in most liquid stock markets (Chapters ref chapter. Heavytraffic and \ref chapter. Price)
Nguyen, Trong Hieu. "Modèles mathématiques de la dynamique des populations en environnement déterministe et stochastique." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066432/document.
Full textIn this thesis, we consider mathematical population dynamics models in deterministic and stochastic environments. For deterministic environments, we study three models: an intraguild model with the effects of spatial heterogeneous environment and fast migration of individuals; a fishery model with Marine Protected Area where fishing is prohibited and an area where the fish population is harvested; a predator-prey model which has one prey and two predators with Beddington-DeAngelis functional responses. For stochastic environments, we study SIRS epidemic model and predator-prey models under telegraph noise. We try to present the dynamical behavior of these models and show out the existence or vanishing of species in the models
Chappet, de Vangel Benoît. "Modèles cellulaires de champs neuronaux dynamiques." Electronic Thesis or Diss., Université de Lorraine, 2016. http://www.theses.fr/2016LORR0194.
Full textIn the constant search for design going beyond the limits of the von Neumann architecture, non conventional computing offers various solutions like neuromorphic engineering and cellular computing. Like von Neumann who roughly reproduced brain structures to design computers architecture, neuromorphic engineering takes its inspiration directly from neurons and synapses using analog substratum. Cellular computing influence comes from natural substratum (chemistry, physic or biology) imposing locality of interactions from which organisation and computation emerge. Research on neural mechanisms was able to demonstrate several emergent properties of the neurons and synapses. One of them is the attractor dynamics described in different frameworks by Amari with the dynamic neural fields (DNF) and Amit and Zhang with the continuous attractor neural networks. These neural fields have various computing properties and are particularly relevant for spatial representations and early stages of visual cortex processing. They were used, for instance, in autonomous robotics, classification and clusterization. Similarly to many neuronal computing models, they are robust to noise and faults and thus are good candidates for noisy hardware computation models which would enable to keep up or surpass the Moore law. Indeed, transistor area reductions is leading to more and more noise and the relaxation of the approx. 0% fault during production and operation of integrated circuits would lead to tremendous savings. Furthermore, progress towards many-cores circuits with more and more cores leads to difficulties due to the centralised computation mode of usual parallel algorithms and their communication bottleneck. Cellular computing is the natural answer to these problems. Based on these different arguments, the goal of this thesis is to enable rich computations and applications of dynamic neural fields on hardware substratum with neuro-cellular models enabling a true locality, decentralization and scalability of the computations. This work is an attempt to go beyond von Neumann architectures by using cellular and neuronal computing principles. However, we will stay in the digital framework by exploring performances of proposed architectures on FPGA. Analog hardware like VLSI would also be very interesting but is not studied here. The main contributions of this work are : 1) Neuromorphic DNF computation ; 2) Local DNF computations with randomly spiking dynamic neural fields (RSDNF model) ; 3) Local and asynchronous DNF computations with cellular arrays of stochastic asynchronous spiking DNFs (CASAS-DNF model)
Chéron, Arnaud. "La dynamique du marché du travail dans les modèles d'équilibre général intemporels stochastiques." Paris 1, 2000. http://www.theses.fr/2000PA010050.
Full textKamber, Güneş. "Essais sur les dynamiques de l'inflation dans les modèles stochastiques d'équilibre général." Paris 1, 2009. http://www.theses.fr/2009PA010036.
Full textChappet, de Vangel Benoît. "Modèles cellulaires de champs neuronaux dynamiques." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0194/document.
Full textIn the constant search for design going beyond the limits of the von Neumann architecture, non conventional computing offers various solutions like neuromorphic engineering and cellular computing. Like von Neumann who roughly reproduced brain structures to design computers architecture, neuromorphic engineering takes its inspiration directly from neurons and synapses using analog substratum. Cellular computing influence comes from natural substratum (chemistry, physic or biology) imposing locality of interactions from which organisation and computation emerge. Research on neural mechanisms was able to demonstrate several emergent properties of the neurons and synapses. One of them is the attractor dynamics described in different frameworks by Amari with the dynamic neural fields (DNF) and Amit and Zhang with the continuous attractor neural networks. These neural fields have various computing properties and are particularly relevant for spatial representations and early stages of visual cortex processing. They were used, for instance, in autonomous robotics, classification and clusterization. Similarly to many neuronal computing models, they are robust to noise and faults and thus are good candidates for noisy hardware computation models which would enable to keep up or surpass the Moore law. Indeed, transistor area reductions is leading to more and more noise and the relaxation of the approx. 0% fault during production and operation of integrated circuits would lead to tremendous savings. Furthermore, progress towards many-cores circuits with more and more cores leads to difficulties due to the centralised computation mode of usual parallel algorithms and their communication bottleneck. Cellular computing is the natural answer to these problems. Based on these different arguments, the goal of this thesis is to enable rich computations and applications of dynamic neural fields on hardware substratum with neuro-cellular models enabling a true locality, decentralization and scalability of the computations. This work is an attempt to go beyond von Neumann architectures by using cellular and neuronal computing principles. However, we will stay in the digital framework by exploring performances of proposed architectures on FPGA. Analog hardware like VLSI would also be very interesting but is not studied here. The main contributions of this work are : 1) Neuromorphic DNF computation ; 2) Local DNF computations with randomly spiking dynamic neural fields (RSDNF model) ; 3) Local and asynchronous DNF computations with cellular arrays of stochastic asynchronous spiking DNFs (CASAS-DNF model)
Mercier, Sophie. "Modèles stochastiques et méthodes numériques pour la fiabilité." Habilitation à diriger des recherches, Université Paris-Est, 2008. http://tel.archives-ouvertes.fr/tel-00368100.
Full textNous nous intéressons ensuite au remplacement préventif de composants devenus obsolescents, du fait de l'apparition de nouveaux composants plus performants. Le problème est ici de déterminer la stratégie optimale de remplacement des anciens composants par les nouveaux. Les résultats obtenus conduisent à des stratégies très différentes selon que les composants ont des taux de panne constants ou non.
Les travaux suivants sont consacrés à l'évaluation numérique de différentes quantités fiabilistes, les unes liées à des sommes de variables aléatoires indépendantes, du type fonction de renouvellement par exemple, les autres liées à des systèmes markoviens ou semi-markoviens. Pour chacune de ces quantités, nous proposons des bornes simples et aisément calculables, dont la précision peut être ajustée en fonction d'un pas de temps. La convergence des bornes est par ailleurs démontrée, et des algorithmes de calcul proposés.
Nous nous intéressons ensuite à des systèmes hybrides, issus de la fiabilité dynamique, dont l'évolution est modélisée à l'aide d'un processus de Markov déterministe par morceaux (PDMP). Pour de tels systèmes, les quantités fiabilistes usuelles ne sont généralement pas atteignables analytiquement et doivent être calculées numériquement. Ces quantités s'exprimant à l'aide des lois marginales du PDMP (les lois à t fixé), nous nous attachons plus spécifiquement à leur évaluation. Pour ce faire, nous commençons par les caractériser comme unique solution d'un système d'équations intégro-différentielles. Puis, partant de ces équations, nous proposons deux schémas de type volumes finis pour les évaluer, l'un explicite, l'autre implicite, dont nous démontrons la convergence. Nous étudions ensuite un cas-test issu de l'industrie gazière, que nous modélisons à l'aide d'un PDMP, et pour lequel nous calculons différentes quantités fiabilistes, d'une part par méthodes de volumes finis, d'autre part par simulations de Monte-Carlo. Nous nous intéressons aussi à des études de sensibilité : les caractéristiques d'un PDMP sont supposées dépendre d'une famille de paramètres et le problème est de comparer l'influence qu'ont ces différents paramètres sur un critère donné, à horizon fini ou infini. Cette étude est faite au travers des dérivées du critère d'étude par rapport aux paramètres, dont nous démontrons l'existence et que nous calculons.
Enfin, nous présentons rapidement les travaux effectués par Margot Desgrouas lors de sa thèse consacrée au comportement asymptotique des PDMP, et nous donnons un aperçu de quelques travaux en cours et autres projets.
Berglund, Nils. "Equations différentielles stochastiques singulièrement perturbées." Habilitation à diriger des recherches, Université du Sud Toulon Var, 2004. http://tel.archives-ouvertes.fr/tel-00004304.
Full textAlimi, Kawther. "Essais sur la politique monétaire en Tunisie dans un cadre d’Équilibre Général Dynamique Stochastique." Thesis, Orléans, 2019. http://www.theses.fr/2019ORLE0502.
Full textIn Tunisia, the authorities had to face many economic challenges in 2011 which marked a real reversal of the economic situation after the popular uprising and the overthrow of the political power in place. Since then, the Central Bank of Tunisia has been at the center of controversy over the role it has played or should play in relation to growth, the reduction of unemployment and price stability. The first chapter analyzes the effects of monetary policy in the context of a high inflationary threat. We show that the effects of the BCT response to inflation have been limited and that the monetary policy instrument has become almost inoperative. It appears that the effectiveness of the CBT's monetary policy was thus limited by other factors such that the sharp depreciation of the dinar observed since 2011 has increased imported inflation. The second chapter deals with the interaction between monetary policy and exchange rate movements. We show that the degree of pass-through has a considerable impact on economic fluctuations in terms of the variability of inflation and the output gap. In line with what was found in the first chapter, the interest rate channelis also inefficient, particularly in the context of incomplete pass-through. Thus, the challenge for the BCT is to stabilize the exchange rate gap in order to improve the effectiveness of monetary policy and limit inflation. Imperfections in the labor market are also likely to explain inflation in Tunisia and difficulties in controlling price increases. In the last chapter, we analyze the effects of monetary policy by considering wage rigidity in the labor market. This chapter shows that wage rigidity largely affects the dynamics of inflation in Tunisia and consequently the effectiveness of monetary policy
Champagnat, Nicolas. "Etude mathématique de modèles stochastiques d'évolution issus de la théorie écologique des dynamiques adaptatives." Paris 10, 2004. http://www.theses.fr/2004PA100138.
Full textThis thesis is interested in the probabilistic study of ecological models belonging to the recent theory of "adaptive dynamics''. After having presented and generalized the scope and the biological heuristics of these models, we obtain a microscopic justification of a jump process modelizing evolution from a measure-valued interacting particle system describing the population dynamics at the individual level. This is a time scale separation result based on two asymptotics: rare mutations and large population. Then, we obtain an ordinary differential equation known as the ``canonical equation of adaptive dynamics'' by applying an asymptotic of small jumps to the preceding process. This limit leads us to introduce a diffusion model of evolution as a diffusion approximation of the jump process, which coefficients present bad regularity properties: discontinuous drift and degenerate diffusion parameter at the same points. We then study the weak existence, uniqueness in law and strong Markov property for this process, which are linked to the question whether this diffusion can reach particular isolated points of the space in finite time or not. Finally, we prove a large deviations principle for these degenerate diffusions, allowing to study the problem of diffusion exit from an attracting domain, which is a fundamental biological question
Touya, Clément. "Étude de modèles dynamiques pour la transition vitreuse." Toulouse 3, 2009. http://thesesups.ups-tlse.fr/1017/.
Full textThis thesis details the study of dynamical models in the framework of the glass transition. A full understanding of this phenomenon is still eluding modern physics. By means of toy model's, we thus study some properties which are typical of this transition. For example, when you come close to the transition, the relaxation dynamic of the system slows down dramatically. In order to study those systems, truly out of equilibrium, the main paradigm we use in this thesis is the disordered systems. Indeed, under some circumstances, an analogie exists between a model with disorder, and a real system which exhibit a true structural glass transition. If the interaction is short ranged, the relaxation time can be linked to the diffusion constant of the medium. If it vanishes, we have then a crossover between a diffusive and a sub-diffusive regime. This dynamical transition is then similar to the glass transition. In this spirit, we focused on the study of dipoles diffusing in a random electrical field. In this model, the disorder is given by the random electrical potential which gives birth to the field, and the most natural choice is then to take a Gaussian statistic for the potential. In an adiabatique limit, where the dipole adapt instantaneously to the local field, the model just reduces to a particle diffusing in a squared Gaussian effective potential. We show here, exactly in one dimension, and through a renormalization group analysis in higher dimension, that the diffusion constant vanishes for a critical non-zero temperature where the dynamic get frozen like in real glass. We show also that beyond this adiabatique approximation, the transition remain at the same critical temperature in one dimension
Champagnat, Nicolas. "Étude mathématique de modèles stochastiques d'évolution issus de la théorie écologique des dynamiques adaptatives." Phd thesis, Université de Nanterre - Paris X, 2004. http://tel.archives-ouvertes.fr/tel-00091929.
Full textBenchimol, Jonathan. "Modèles nouveaux keynésiens dynamiques et stochastiques en équilibre général, monnaie et aversion au risque." Paris 1, 2011. https://tel.archives-ouvertes.fr/tel-00672439.
Full textBourrel, Emmanuel. "Modélisation dynamique de l'écoulement du trafic routier : du macroscopique au microscopique." Lyon, INSA, 2003. http://theses.insa-lyon.fr/publication/2003ISAL0073/these.pdf.
Full textTo satisfy road managers needs (in particular in terms of decision-making and evaluation of their actions of exploitation), many dynamic traffic flow models have been developed in order to represent propagation of vehicles on a road section. Those models describe traffic flow in a more or less aggregated way and are generally classified into two main groups: microscopic models, which are interested in the dynamics of individualized vehicles, and macroscopic models, more aggregated models which describe traffic as a fluid. One of the difficulties encountered in the study of those models is the great disparity of scales to be considered. The aim of this thesis is to look further into these scales problems (in particular by studying the link that exists between microscopic and macroscopic models) through the development of a hybrid model of traffic flow (a hybrid model is defined as the coupling between a microscopic model and a macroscopic model). The interest of a hybrid model is that it makes it possible to adapt the traffic flow model to the needs to model the various elements of a network. It is thus possible to describe some specific elements where the local phenomena of traffic flow can have global consequences with the microscopic model(toll station, on-ramp, roundabout. . . ) while preserving a global vision of the flow on the rest of the network with the macroscopic model. Although there are some models of this type in the literature, there is no global view of the problems related to hybridization. So it is very difficult to judge the relevance of existing models. This is why we propose in this thesis a general theoretical framework defining these models, in particular by determining the fundamental properties that a hybrid models must have to be valid. We then propose a new hybrid model based on a first order macroscopic model (the Lighthill-Whitham- Richards model). The characteristic of that model is that it makes it possible to take into account the diversity of vehicles behaviour in the microscopic part by introducing distributions on some parameters. The results provided by this model are then studied for three examples of application (one-way toll station, crossing between a major and a minor road, combination of two intersections) in which we show the interest of the coupling between microscopic and macroscopic models
Andrieux, Arnaud. "Estimation de l'adhérence mobilisable des véhicules : application à la dynamique longitudinale." Troyes, 2009. http://www.theses.fr/2009TROY0006.
Full textTo warn of the loss in control of a vehicle on a slippery surface, the driver must be warned when his driving does not guarantee him anymore safety. So, for a given pneumatic-roadway configuration, the actual friction u must be measured and compared with the potential maximum friction umax. Car implemented estimation of umax for low stresses requires precise measurement of the longitudinal slip rate k and the longitudinal friction coefficient u. To obtain k, a signal processing method is proposed to eliminate the deterministic component of the measurement noise on speed signals. To obtain u, a calculation method based on support vector machines (SVM) is used. These techniques are then implemented on a test vehicle to develop an experimental method allowing to obtain curves u =f (k). A trial campaign allowed varying several parameters of the pneumatic-roadway contact. The results show the influence of the tire and the road on the appearance of curves u =f (k). They also show the impossibility to estimate umax only from the longitudinal stiffness of the pneumatic-roadway contact, countering some results issued from the literature. Nevertheless a predictor of umax based on a priori knowledge of the pneumatic-roadway contact is introduced
Adam, Etienne. "Persistance et vitesse d'extinction pour des modèles de populations stochastiques multitypes en temps discret." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLX019/document.
Full textThis thesis is devoted to the mathematical study of stochastic modelds of structured populations dynamics.In the first chapter, we introduce a discrete time stochastic process taking into account various ecological interactions between individuals, such as competition, migration, mutation, or predation. We first prove a ``law of large numbers'': where we show that if the initial population tends to infinity, then, on any finite interval of time, the stochastic process converges in probability to an underlying deterministic process. We also quantify the discrepancy between these two processes by a kind of ``central limit theorem''. Finally, we give a criterion of persistence/extinction in order to determine the long time behavior of the process. This criterion highlights a critical case which will be studied in more detail in the following chapters.In the second chapter, we give a criterion for the possible unlimited growth in the critical case mentioned above. We apply this criterion to the example of a source-sink metapopulation with two patches of type source, textit{i.e.} the population of each patch goes to extinction if we do not take into account the migration. We prove that there is a possible survival of the metapopulation.In the third chapter, we focus on the behavior of our critical process when it tends to infinity. We prove a convergence in distribution of the scaled process to a gamma distribution, and in a more general framework, by also rescaling time, we obtain a distribution limit of a function of our process to the solution of a stochastic differential equation called a squared Bessel process.In the fourth and last chapter, we study hitting times of some compact sets when our process does not tend to infinity. We give nearly optimal bounds for the tail of these hitting times. If the process goes to extinction almost surely, we deduce from these bounds precise estimates of the tail of the extinction time. Moreover, if the process is a Markov chain, we give a criterion of null recurrence or positive recurrence and in the latter case, we obtain a subgeometric convergence of its transition kernel to its invariant probability measure
Tran, Viet Chi. "Modèles particulaires stochastiques pour des problèmes d'évolution adaptative et pour l'approximation de solutions statistiques." Phd thesis, Université de Nanterre - Paris X, 2006. http://tel.archives-ouvertes.fr/tel-00125100.
Full textOmrani, Walid. "Dynamique des taux de change et mémoire longue." Paris 10, 2005. http://www.theses.fr/2005PA100034.
Full textThe objective of this thesis is double. The first objective is modelling the complex dynamics that governs daily returns of exchange rates of the G7 as well as their conditional volatilities. We will try to propose an econometric model able to take account of a long memory component simultaneously in the conditional mean and a second component long memory in the equation of the conditional volatility. The second objective of this thesis is to show the superiority of the approach based on long memory processes in relation to the linear approach, vis-a-vis of the survey of the efficiency theory to the weak sense. It is also about putting in evidence the importance of the modelling of the conditional variance and his/her/its contribution to this theory. The second objective of this thesis is to show the superiority of the approach based on processes to long memory in relation to the linear approach, vis-a-vis of the survey of the efficiency theory. Also, we show the importance of the modelling of the conditional variance and its contribution to this theory
Lèbre, Sophie. "Analyse de processus stochastiques pour la génomique : étude du modèle MTD et inférence de réseaux bayésiens dynamiques." Evry-Val d'Essonne, 2007. http://www.biblio.univ-evry.fr/theses/2007/interne/2007EVRY0017.pdf.
Full textThis thesis deals with DNA sequence and time series gene expression analysis. First we study the parsimonious Markov model called Mixture Transition Distribution (MTD) model and introduce an EM algorithm for MTD models estimation. Then we propose two approaches for genetic network recovering using Dynamic Bayesian Networks (DBNs). The dependencies are described by a directed graph whose topology has to be inferred despite the overly low number of repeated measurements compared with the number of observed genes. First we assume that the topology is constant across time, we approximate this graph by considering partial order dependencies and we develop a deterministic procedure for DBNs inference. Then we consider a multiple changepoint regression model defining a succession of homogeneous phases. The changepoints location and the structure within each phase are simultaneously inferred thanks to a reversible jump MCMC procedure
Delattre, Maud. "Inférence statistique dans les modèles mixtes à dynamique Markovienne." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00765708.
Full textCottereau, Régis. "Probalilistic models of impedance matrices : application to dynamic soil-structure interaction." Châtenay-Malabry, Ecole centrale de Paris, 2006. http://www.theses.fr/2006ECAP1034.
Full textIn many application fields, as in civil engineering or aeronautics, engineers have to deal with design problems where the structure is coupled to an unbounded domain. For these problems, only the structure is of interest, and the behavior of the exterior domain is taken into account through its equivalent stiffness, in statics, or its impedance matrix, in dynamics. The models for the unbounded domains considered in these applications are usually coarse and the information available on their properties scarse and polluted. This leads to errors in the estimation of the behavior of the structure, which may partially be taken into account by using probabilistic approaches. We present, in this Ph. D. Thesis a probabilistic model of impedance matrices, which generalizes the nonparametric approaches introduced recently by Soize for the predictions of vibrations in random structures. The construction of this probabilistic model first requires the construction of a deterministic model, so-called hidden variables model, that verifies the basic properties of impedance matrices, among which the causality. The hidden variables model has to be identified from numerical results or experimental measures, and the identification procedure is also developed in this thesis. Two applications are presented. Our nonparametric model of the impedance matrix is first compared to a parametric model, on a classical problem in dynamic soil-structure interaction, to illustrate the main differences between the two approaches. Then, it is used in a more industrial seismic design problem, to show the practical application of the nonparamatric probabilistic model of impedance matrices
Pichené, Matthieu. "Analyse multi-niveaux en biologie systémique computationnelle : le cas des cellules HeLa sous traitement apoptotique." Thesis, Rennes 1, 2018. http://www.theses.fr/2018REN1S026/document.
Full textThis thesis examines a new way to study the impact of a given pathway on the dynamics of a tissue through Multi-Level Analysis. The analysis is split in two main parts: The first part considers models describing the pathway at the cellular level. Using these models, one can compute in a tractable manner the dynamics of a group of cells, representing it by a multivariate distribution over concentrations of key molecules. % of the distribution of the states of this pathway through groups of cells. The second part proposes a 3d model of tissular growth that considers the population of cell as a set of subpopulations, partitionned such as each subpopulation shares the same external conditions. For each subpopulation, the tractable model presented in the first part can be used. This thesis focuses mainly on the first part, whereas a chapter covers a draft of a model for the second part
Arnoux, Adrien. "Réduction des modèles numériques en dynamique linéaire basse fréquence des automobiles." Thesis, Paris Est, 2012. http://www.theses.fr/2012PEST1019/document.
Full textThe objective of this research is to construct a reduced-order model to predict the dynamical response, in the LF band, of the stiff parts of a complete automotive vehicle in order to facilitate the draft design. The vehicles under consideration have many elastic modes in LF due to the presence of many flexible parts and equipments. To build such a model, we introduced a non-usual basis of the admissible space of global displacements. The construction of this basis requires the decomposition of the domain of the structure. This subdomain decomposition is performed by using the Fast Marching Method that we have extended to take into account the high complexity of the mesh of an automotive vehicle. Then the matrix equations of the FE model are projected on this basis. To take into account the system parameters uncertainties, the model uncertainties induced by the modeling errors and finally, the uncertainties related to the neglecting of local contributions in the reduced-order model, a nonparametric probabilistic model of the three sources of uncertainties has been implemented on the reduced-order model constructed with the global displacements eigenvectors. The dispersion parameters of the probabilistic model are identified using the maximum likelihood method and the responses obtained from a stochastic reference model which includes experimental data resulting from previous works. This stochastic model which has been designed for the prediction of the global displacements of the rigid parts in the LF band is validated on a simple structure of an automotive model and has been successfully applied on a complete model of automotive vehicle
Berro, Julien. "Du monomère à la cellule : modèle de la dynamique de l'actine." Université Joseph Fourier (Grenoble), 2006. http://www.theses.fr/2006GRE10226.
Full textActin filaments are biological polymers that are very abundant in eucaryot cytoskeleton. Their auto-assembly and auto-organization are highly dynami. And are essential in cell motility and membrane deformations. Ln this thesis we propose three approaches, on different scales, in order to enlighten mechanisms for the regulation ofassembly of, organization of and production of force by biological filaments such as actin filaments. First, we have developed a stochastic multi-agent simulation tool for studying biological filaments taking into consideration interactions on the nanometer scale. This new tool allowed us to bring out the acceleration of actin monomer turnover due to fragmentation of filaments by ADF/Cofilin and the symmetry breaking induced by thisprotein, which agree weil with experimental data from L. Blanchoin team (CEA Grenoble). Secondly, we studied a continuou model for filament buckling, providing, on the one hand, an estimation of forces exerted in vitro or in vivo with respect to extremity attachment conditions and, on the other hand, limit conditions for buckling. Thirdly, we developed a framework for organizing kinetic biochemical data from reaction networks, which was used for the regulation of actin polymerization. These three modeling approaches improved the knowledge on actin dynamics and are useful complements for experimental approaches in biology
Homman, Ahmed. "Développement de schémas numériques d’intégration de méthodes multi-échelles." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1040/document.
Full textThis thesis is about the development and analysis of numerical schemes forthe integration of the Dissipative Particle Dynamics with Energy conservation. A presentation and a weak convergence analysis of existing schemes is performed, as well as the introduction and a similar analysis of two new straightforwardly parallelizable schemes. The energy preservation properties of all these schemes are studied followed by a comparative study of their biases on the estimation of the average values of physical observables on equilibrium simulations. The schemes are then tested on shock simulations of DPDE fluids, where we show that our schemes bring an improvement on the accuracy of the description of the behavior of such systems compared to existing straightforwardly parallelizable schemes. Finally, we present an attempt at accelerating a reference DPDE integration scheme on sequential simulations
Reype, Christophe. "Modélisation probabiliste et inférence bayésienne pour l’analyse de la dynamique des mélanges de fluides géologiques : détection des structures et estimation des paramètres." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0235.
Full textThe analysis of hydrogeochemical data aims to improve the understanding of mass transfer in the sub-surface and the Earth’s crust. This work focuses on the study of fluid-fluid interactions through fluid mixing systems, and more particularly on the detection of the compositions of the mixing sources. The detection is done by means of a point process: the proposed model is unsupervised and applicable to multidimensional data. Physical knowledge of the mixtures and geological knowledge of the data are directly integrated into the probability density of a Gibbs point process, which distributes point patterns in the data space, called the HUG model. The detected sources form the point pattern that maximises the probability density of the HUG model. This probability density is known up to the normalization constant. The knowledge related to the parameters of the model, either acquired experimentally or by using inference methods, is integrated in the method under the form of prior distributions. The configuration of the sources is obtained by a simulated annealing algorithm and Markov Chain Monte Carlo (MCMC) methods. The parameters of the model are estimated by an approximate Bayesian computation method (ABC). First, the model is applied to synthetic data, and then to real data. The parameters of the model are then estimated for a synthetic data set with known sources. Finally, the sensitivity of the model to data uncertainties, to parameters choices and to algorithms set-up is studied