In the first half of this thesis, we extend the results of Halfin and Whitt to generally distributed service times. This is accomplished by first writing the system equations for the G/GI/N queue in a manner similar to the system equations for G/GI/Infinity queue. We next identify a key relationship between these two queues. This relationship allows us to leverage several existing results for the G/GI/Infinity queue in order to prove our main result. Our main result in the first part of this thesis is to show that the diffusion scaled queue length process for the G/GI/N queue in the Halfin-Whitt regime converges to a limiting stochastic process which is driven by a Gaussian process and satisfies a stochastic convolution equation. We also show that a similar result holds true for the fluid scaled queue length process under general initial conditions. Customer abandonment is also a common feature of many call centers. Some researchers have even gone so far as to suggest that the level of customer abandonment is the single most important metric with regards to a call center's performance. In the second half of this thesis, we improve upon a result of Ward and Glynn's concerning the GI/GI/1+GI queue in heavy traffic. Whereas Ward and Glynn obtain a diffusion limit result for the GI/GI/1+GI queue in heavy traffic which incorporates only the density the abandonment distribution at the origin, our result incorporate the entire abandonment distribution. This is accomplished by a scaling the hazard rate function of the abandonment distribution as the system moves into heavy traffic. Our main results are to obtain diffusion limits for the properly scaled workload and queue length processes in the GI/GI/1+GI queue. The limiting diffusions we obtain are reflected at the origin with a negative drift which is dependent upon the hazard rate of the abandonment distribution. Because these diffusions have an analytically tractable steady-state distribution, they can be used to provide a closed-form approximation for the steady-state distribution of the queue length and workload processes in a GI/GI/1+GI queue. We demonstrate the accuracy of these approximations through simulation.

The Generalized Sidelobe Canceller is an adaptive algorithm for optimally estimating the parameters for beamforming, the signal processing technique of combining data from an array of sensors to improve SNR at a point in space. This work focuses on the algorithm’s application to widely-separated microphone arrays with irregular distributions used for human voice capture. Methods are presented for improving the performance of the algorithm’s blocking matrix, a stage that creates a noise reference for elimination, by proposing a stochastic model for amplitude correction and enhanced use of cross correlation for phase correction and time-difference of arrival estimation via a correlation coefficient threshold. This correlation technique is also applied to a multilateration algorithm for an efficient method of explicit target tracking. In addition, the underlying microphone array geometry is studied with parameters and guidelines for evaluation proposed. Finally, an analysis of the stability of the system is performed with respect to its adaptation parameters.

No contexto das teorias de perturbação estocástica, analisamos a acurácia de dois modelos poroelásticos lineares aplicados a meios porosos altamente heterogêneos sujeitos as incertezas na permeabilidade e nas constantes elásticas. Os modelos poroelásticos completamente e fracamente acoplados analisados surgem caracterizados pelo grau de intensidade de acoplamento entre a hidrodinámica governante da percolação o do fluido e a poromecânica que rege as deformações da matriz porosa. Novas equações efetivas para os momentos das soluções são obtidas fazendo uso de técnicas de expansão assintótica. À luz da teoria de perturbação, são estabelecidas hipóteses simplificadoras que elucidam o domínio de validade do modelo fracamente acoplado, amplamente utilizado nos simuladores de Reservatórios de Petróleo, na presença de heterogeneidades e correlação nos coeficientes poroelásticos. Simulações computacionais do processo de extração primária de petróleo são realizadas utilizando técnicas de Monte Carlo em conjunção com métodos de elementos finitos. Resultados numéricos obtidos confirmam claramente a conjectura estabelecida pela teoria de perturbação relacionada com a inacurácia do modelo fracamente acoplado na presença de variabilidade nas constantes elásticas. A metodologia empregada permite quantificar a distância entre os dois modelos poroelásticos, e consequentemente, propor a escolha do modelo apropriado para diferentes condições de carregamento e variabilidade da formação geológica. / In the context of the stochastic perturbations theories we analyze the accuracy of two linear poroelastic models applied to highly heterogeneous porous media subject to uncertainties in the permeability and the elastic constants. The poroelastic models completely and weakly coupled analized arise characterized by the degree of intensity coupling between the hydrodinamics, governor of the percolation of the fluid and poromechanics which governs the deformation of the porous matrix. New equations for the moments of effective solutions using techniques of asymptotic expansion. In light of the perturbation theory are set simplifying assumptions that clarify clearly the domain of validity of weakly coupled model, widely used in simulation of oil reservoirs in the presence of heterogeneities and correlation in poroelastic coefficients. Computational simulations of the primary extraction of oil process are carried out using Monte Carlo techniques in conjunction with finite element methods. Results obtained clearly confirm the conjecture established by the perturbation theorie related with the inaccuracy of the weakly coupled model in the presence of variability in the elastic constants. The methodology used allows to quantify the distance between the two poroelastics models and therefore propose the appropriate model for different conditions of loading and variability of the geological formation.

The recent observed growth in the diffusion of Special Purpose Acquisition Companies phenomena on the U.S stock market may be analyzed from a mathematical standpoint, where different approaches of the Bass Diffusion Model might be utilized. The Bass diffusion model originates from analysis of product diffusion, where only a few applications have been seen by financial scholars. The thesis takes a multi analytical approach to examine the phenomena, where multiple regression analysis and Bayesian statistics are used in the parameter estimation processes. Estimated parameter are applied in three different scenarios of expressing the Bass diffusion model in a discrete time state. By utilizing these different approaches that arise, the study shows that the diffusion of Special Purpose Acquisition Companies Initial Public Offerings in fact can be analyzed from a mathematical standpoint utilizing the Bass diffusion model. Some approaches and scenarios indicate better results in terms of fitting the diffusion, while purposing practical actualities towards the reader and market practitioners. The study further purposes potential modifications that might improve the results of fitting the phenomena

Nous déterminons d’abord l’impact d’un plan infini réfléchissant sur l’espace occupé par une marche brownienne bidimensionnelle à un temps fixé, que nous caractérisons par le périmètre moyen de son enveloppe convexe (plus petit polygone convexe contenant toute la trajectoire). Nous déterminons également la longueur moyenne de la portion du plan visitée par le marcheur, et la probabilité de survie d’un marcheur brownien dans un secteur angulaire absorbant.Nous étudions ensuite le temps mis par un marcheur sur réseau pour visiter tous les sites d’un volume, ou une partie d’entre eux. Nous calculons la moyenne de ce temps, dit de couverture, à une dimension pour une marche aléatoire persistante. Nous déterminons également la distribution du temps de couverture et d’autres observables assimilées pour la classe des processus non compacts, qui décrivent un large spectre de recherches aléatoires.Dans un troisième temps, nous calculons et analysons la probabilité de sortie conditionnelle d’un marcheur brownien évoluant dans un intervalle se dilatant ou se contractant à vitesse constante.Enfin, nous étudions plusieurs aspects du modèle du marcheur aléatoire “affamé”, qui meurt si les visites de nouveaux sites, grâce auxquelles il engrange des ressources, ne sont pas suffisamment regulières. Nous en proposons un traitement de type champ moyen à deux dimensions, puis nous déterminons l’impact de la régénération des ressources sur les propriétés de survie du marcheur. Nous considérons finalement un modèle d’exploitation de parcelles de nourriture prenant explicitement en compte le mouvement du marcheur, qui se ramène de manière naturelle au modèle du marcheur aléatoire affamé. / We first determine the impact of an infinite reflecting wall on the space occupied by a planar Brownian motion at a fixed observation time. We characterize it by the mean perimeter of its convex hull, defined as the minimal convex polygon enclosing the whole trajectory. We also determine the mean length of the visited portion of the wall, and the survival probability of a Brownian walker in an absorbing wedge.We then study the time needed for a lattice random walker to visit every site of a confined volume, or a fraction of them. We calculate the mean value of this so-called cover time in one dimension for a persistant random walk. We also determine the distribution of the cover time and related observables for the class of non compact processes, which describes a wide range of random searches.After that, we calculate and analyze the splitting probability of a one-dimensional Brownian walker evolving in an expanding or contracting interval.Last, we study several aspects of the model of starving random walk, where the walker starves if its visits to new sites, from which it collects resources, are not regular enough. We develop a mean-field treatment of this model in two dimensions, then determine the impact of regeneration of resources on the survival properties of the walker. We finally consider a model of exploitation of food patches taking explicitly into account the displacement of the walker in the patches, which can be mapped onto the starving random walk model.

<p>This thesis investigates the second-best toll pricing and capacity expansion problems when stated as mathematical programs with equilibrium constraints (MPEC). Three main questions are rised: First, whether conventional descent methods give sufficiently good solutions, or whether global solution methods are to prefer. Second, how the performance of the considered solution methods scale with network size. Third, how a discretized stochastic mathematical program with equilibrium constraints (SMPEC) formulation of a stochastic network design problem can be practically solved. An attempt to answer these questions is done through a series ofnumerical experiments.</p><p>The traffic system is modeled using the Wardrop’s principle for user behavior, separable cost functions of BPR- and TU71-type. Also elastic demand is considered for some problem instances.</p><p>Two already developed method approaches are considered: implicit programming and a cutting constraint algorithm. For the implicit programming approach, several methods—both local and global—are applied and for the traffic assignment problem an implementation of the disaggregate simplicial decomposition (DSD) method is used. Regarding the first question concerning local and global methods, our results don’t give a clear answer.</p><p>The results from numerical experiments of both approaches on networks of different sizes shows that the implicit programming approach has potential to solve large-scale problems, while the cutting constraint algorithm scales worse with network size.</p><p>Also for the stochastic extension of the network design problem, the numerical experiments indicate that implicit programming is a good approach to the problem.</p><p>Further, a number of theorems providing sufficient conditions for strong regularity of the traffic assignment solution mapping for OD connectors and BPR cost functions are given.</p>

This thesis investigates the second-best toll pricing and capacity expansion problems when stated as mathematical programs with equilibrium constraints (MPEC). Three main questions are rised: First, whether conventional descent methods give sufficiently good solutions, or whether global solution methods are to prefer. Second, how the performance of the considered solution methods scale with network size. Third, how a discretized stochastic mathematical program with equilibrium constraints (SMPEC) formulation of a stochastic network design problem can be practically solved. An attempt to answer these questions is done through a series ofnumerical experiments. The traffic system is modeled using the Wardrop’s principle for user behavior, separable cost functions of BPR- and TU71-type. Also elastic demand is considered for some problem instances. Two already developed method approaches are considered: implicit programming and a cutting constraint algorithm. For the implicit programming approach, several methods—both local and global—are applied and for the traffic assignment problem an implementation of the disaggregate simplicial decomposition (DSD) method is used. Regarding the first question concerning local and global methods, our results don’t give a clear answer. The results from numerical experiments of both approaches on networks of different sizes shows that the implicit programming approach has potential to solve large-scale problems, while the cutting constraint algorithm scales worse with network size. Also for the stochastic extension of the network design problem, the numerical experiments indicate that implicit programming is a good approach to the problem. Further, a number of theorems providing sufficient conditions for strong regularity of the traffic assignment solution mapping for OD connectors and BPR cost functions are given.

The subject of this thesis is to control the storage function of the reservoir using artificial intelligence methods, including the construction of the appropriate control algorithm. The thesis is divided into the theoretical part and the part of the application of reservoir storage function control. The theoretical part describes the control algorithm and the prediction model. The following are basic optimization methods and artificial intelligence methods. The second part presents the historical data used for the prediction model. The following is a description of calibration and validation of the control module and evaluation of the application results. Finally, there is a comparison and summary of individual results, control algorithm and prediction model. According to the results, the control algorithm can be recommended for further investigation.

Les méthodes géophysiques aéroportées sont très utilisées pour la prospection du sous-sol à l'échelle régionale, permettant ainsi de couvrir de grandes surfaces en particulier les zones difficiles d'accès. Le sujet de thèse concerne le développement de techniques d'interprétation des données géophysiques pour le problème des ressources naturelles et de l'environnement. La première partie de cette thèse concerne le développement d'une méthode de calcul direct des composantes des champs gravimétrique et magnétique à partir d'une structure (corps) géologique modélisé(e) par une grille à base de tétraèdres, ce qui permet de représenter des modèles géologiques très complexes particulièrement en présence de zones faillées et hétérogènes avec un nombre d'éléments optimal. Plusieurs techniques d'inversions utilisent des contraintes mathématiques pour la résolution du problème inverse en modélisation. Ces contraintes permettent de réduire le nombre de modèles possibles. Cependant les solutions proposées appelées aussi « le modèle le plus probable » présentent des solutions lisses, ce qui est loin de représenter la réalité géologique. Pour éluder ce problème, les deuxièmes et troisièmes parties de la thèse proposent des améliorations majeures du processus d'inversion par l'utilisation des méthodes géostatistiques telles que la Simulation Gaussienne Séquentielle ou la Co-Simulation dans le cas d'une inversion conjointe afin d'estimer les probabilités a posteriori des modèles simulés. La quatrième partie de ce mémoire présente une alternative à la simulation de plusieurs variables. L'apprentissage du réseau de neurones supervisé par un certain nombre de points permet d'établir une relation entre les différentes variables / In recent years with the technology developments, airborne geophysical methods (gravity, magnetic, and electromagnetic) are widely used in the natural resource exploration at the regional scale. It covers large areas particularly in the areas with difficult access. The first part of this thesis consist on the development of new forward modeling algorithm for the calculation of the components of the gravity and magnetic fields based on a tetrahedron grid. The tetrahedral mesh allows the representation of very complex geological models holding many heterogeneous and faulted zones with an optimal number of elements, this reduces significantly the time calculation. Several inversion techniques use mathematical constraints for the resolution of the inverse problem in order to reduce the number of possible models. However the proposed solutions called also "the most probable model" provide a smooth solutions that cannot represent the geological reality. To circumvent this problem in the second and the third parts of this thesis, we made two major improvements. The first, we integrate Sequential Gaussian Simulation into the inversion procedure to determine a possible distributions of a single property. The second is that we used the Co-Simulation in the case of joint inversion to estimate a posteriori probabilities of the simulated models. The last part of this thesis presents an alternative to the several variables simulation, supervised learning of neural networks allows to establish a relationship between the different variables

Die vorliegende Arbeit befasst sich mit einer Reihe von Fragestellungen, die Forschungsfeldern wie rauschinduziertem Verhalten, Strukturbildung in aktiven Medien und Synchronisation nichlinearer Oszillatoren erwachsen. Die verwendeten nichtlinearen Modelle verfügen über erregbare, oszillatorische und bistabile Eigenschaften. Zusätzliche stochastische Fluktuationen tragen wesentlich zur Entstehung komplexer Dynamik bei. Modelliert wird, auf welche Weise sich extrazelluläre Kaliumkonzentration, gespeist von umliegenden Neuronen, auf die Aktivität dieser Neuronen auswirkt. Neben lokaler Dynamik wird die Ausbildung ausgedehnter Strukturen in einem heterogenem Medium analysiert. Die raum-zeitlichen Muster umfassen sowohl Wellenfronten und Spiralen als auch ungewöhnliche Strukturen, wie wandernde Cluster oder invertierte Wellen. Eine wesentliche Rolle bei der Ausprägung solcher Strukturen spielen die Randbedingungen des Systems. Sowohl für diskret gekoppelte bistabile Elemente als auch für kontinuierliche Fronten werden Methoden zur Berechnung von Frontgeschwindigkeiten bei fixierten Rändern vorgestellt. Typische Bifurkationen werden quantifiziert und diskutiert. Der Rückkopplungsmechanismus aus dem Modell neuronaler Einheiten und deren passiver Umgebung kann weiter abstrahiert werden. Ein Zweizustandsmodell wird über zwei Wartezeitverteilungen definiert, welche erregbares Verhalten widerspiegeln. Untersucht wird die instantane und die zeitverzögerte Antwort des Ensembles auf die Rückkopplung. Im Fall von Zeitverzögerung tritt eine Hopf-Bifurkation auf, die zu Oszillationen der mittleren Gesamtaktivität führt. Das letzte Kapitel befasst sich mit Diffusion und Transport von Brownschen Teilchen in einem raum-zeiltich periodischen Potential. Wieder sind es Synchronisationsmechanismen, die nahezu streuungsfreien Transport ermöglichen können. Für eine erhöhte effektiven Diffusion gelangen wir zu einer Abschätzung der maximierenden Parameter. / In this work problems are investigated that arises from resarch fields of noise induced dynamics, pattern formation in active media and synchronisation of self-sustained oscillators. The applied model systems exhibit excitable, oscillatory and bistable behavior as basic modes of nonlinear dynamics. Addition of stochastic fluctuations contribute to the appearance of complex behavior. The extracellular potassium concentration fed by surrounding activated neurons and the feeback to these neurons is modelled. Beside considering the local behavior, nucleation of spatially extended structures is studied. We find typical fronts and spirales as well as unusal patterns such as moving clusters and inverted waves. The boundary conditions of the considered system play an essential role in the formation process of such structures. We present methods to find expressions of the front velocity for discretely coupled bistable units as well as for the countinus front interacting with boundary values. Canonical bifurcation scenarios can be quantified. The feedback mechanism from the model for neuronal units can be generalized further. A two-state model is defined by two waiting time distributions representing excitable dynamics. We analyse the instantaneous and delayed response of the ensemble. In the case of delayed feedback a Hopf-bifurcation occur which lead to oscillations of the mean activity. In the last chapter the transport and diffusion of Brownian particles in a spatio-temporal oscillating potential is discussed. As a cause of nearly dispersionless transport synchronisations mechanisms can be identified. We find an estimation for parameter values which maximizes the effective diiffusion.