Literatura académica sobre el tema "Structures de données probabilistes"
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Artículos de revistas sobre el tema "Structures de données probabilistes"
Areni, Charles S. "Modèle propositionnel probabiliste de la structure de l'argument et de l'acceptation du message". Recherche et Applications en Marketing (French Edition) 18, n.º 1 (marzo de 2003): 95–121. http://dx.doi.org/10.1177/076737010301800105.
Texto completoFlorescu, Liviu. "Structures syntopogènes probabilistes". Publicationes Mathematicae Debrecen 28, n.º 1-2 (1 de julio de 2022): 15–24. http://dx.doi.org/10.5486/pmd.1981.28.1-2.03.
Texto completoBOUDON, Raymond. "Les statistiques peuvent-elles donner une image réelle de la réalité sociale?" Sociologie et sociétés 8, n.º 2 (30 de septiembre de 2002): 141–56. http://dx.doi.org/10.7202/001080ar.
Texto completoLi, Haizhou, François Pinet y Farouk Toumani. "Test de simulation pour les processus métiers centrés données probabilistes". Ingénierie des systèmes d'information 19, n.º 4 (28 de agosto de 2014): 35–60. http://dx.doi.org/10.3166/isi.19.4.35-60.
Texto completoMaranda, Pierre. "Cartographie sémantique : esquisse sémiographique de la Québécoise". Cahiers de géographie du Québec 25, n.º 64 (12 de abril de 2005): 71–86. http://dx.doi.org/10.7202/021506ar.
Texto completoStepanov, Aleksandr. "Le recours à l’évidence dans l’élaboration des normes internes". Civitas Europa N° 51, n.º 2 (14 de junio de 2024): 49–59. http://dx.doi.org/10.3917/civit.051.0049.
Texto completoGnacadja, Claude, Armel Mouketou, Ephrem Nzangue, Chamfort Biroungou y Jacques François Mavoungou. "Analyse de Quelques Caractéristiques de la Filière Maraichage dans Trois Provinces du Gabon". European Scientific Journal, ESJ 18, n.º 27 (31 de agosto de 2022): 296. http://dx.doi.org/10.19044/esj.2022.v18n27p296.
Texto completoHantrais, Linda y Marie-Thérèse Letablier. "Données démographiques et structures familiales". Informations sociales 124, n.º 4 (2005): 16. http://dx.doi.org/10.3917/inso.124.0016.
Texto completoZhang, Yi y Stéphane Commend. "Calculs probabilistes des déplacements dus à la réalisation de tunnels à l’aide d’un modèle aux éléments finis". Revue Française de Géotechnique, n.º 167 (2021): 5. http://dx.doi.org/10.1051/geotech/2021018.
Texto completoClément Maria. "Algorithmes et structures de données en topologie algorithmique". Bulletin 1024, n.º 8 (abril de 2016): 125–27. http://dx.doi.org/10.48556/sif.1024.8.125.
Texto completoTesis sobre el tema "Structures de données probabilistes"
Perrin, Frédéric. "Prise en compte des données expérimentales dans les modèles probabilistes pour la prévision de la durée de vie des structures". Clermont-Ferrand 2, 2008. http://www.theses.fr/2008CLF21823.
Texto completoEl, Abri Marwa. "Probabilistic relational models learning from graph databases". Thesis, Nantes, 2018. http://www.theses.fr/2018NANT4019/document.
Texto completoHistorically, Probabilistic Graphical Models (PGMs) are a solution for learning from uncertain and flat data, also called propositional data or attributevalue representations. In the early 2000s, great interest was addressed to the processing of relational data which includes a large number of objects participating in different relations. Probabilistic Relational Models (PRMs) present an extension of PGMs to the relational context. With the rise of the internet, numerous technological innovations and web applications are driving the dramatic increase of various and complex data. Consequently, Big Data has emerged. Several types of data stores have been created to manage this new data, including the graph databases. Recently there has been an increasing interest in graph databases to model objects and interactions. However, all PRMs structure learning use wellstructured data that are stored in relational databases. Graph databases are unstructured and schema-free data stores. Edges between nodes can have various signatures. Since, relationships that do not correspond to an ER model could be depicted in the database instance. These relationships are considered as exceptions. In this thesis, we are interested by this type of data stores. Also, we study two kinds of PRMs namely, Direct Acyclic Probabilistic Entity Relationship (DAPER) and Markov Logic Networks (MLNs). We propose two significant contributions. First, an approach to learn DAPERs from partially structured graph databases. A second approach consists to benefit from first-order logic to learn DAPERs using MLN framework to take into account the exceptions that are dropped during DAPER learning. We are conducting experimental studies to compare our proposed methods with existing approaches
Fekete, Eric. "Etude probabiliste d'arbres issus de l'algorithmique". Versailles-St Quentin en Yvelines, 2007. http://www.theses.fr/2007VERS0016.
Texto completoThe aim of this thesis is the study of the behavior of trees used in analysis of algorithms. We use probabilistic techniques to study various random objects connected with trees. We formally define the trees we deal with and introduce our main results in chapter one. Each of the three other parts of the thesis contains a specific random phenomenon. We first establish a result on the asymptotics of the rescaled occupation measure of a branching random walk on binary search trees (BSTs). Under weak hypothesis on the increments, we show that this measure converges to a deterministic measure depending on the stable law whose domain of attraction contains the law of the increments. The proof is based on some fundamental properties of the structure of BST. One of them is the result by Louchard on the height of a typical node. This convergence allows to obtain results on two other objects associated to the BST : homogeneous fragmentations of ]0, 1[ and recursive trees. The second study is also on BSTs. We study the profile of the tree (number of leaves at each level) specifying the types of the leaves : arms are the leaves whose brother is an internal node and feet are the leaves whose brother is also a leaf. We use a vector whose coordinates are the level polynomials of arms and feet. The coefficient of order k of these polynomials is the number of arms and feet at level k in the BST of size n. Comparing the two projections of this vector on the eigenspaces of a so-called evolution matrix, we obtain an almost sure and a L2-convergence of a martingale vector, connected to the profile, to a vector associated to the limit of the Jabbour martingale. Finally, the last part deals with another kind of random trees : the suffix trees. These trees are defined from an infinite word and its randomness is given by the source that creates the word. Here we are concerned with -mixing sources. We prove that the fill-up level of a suffix tree with n keys, normalized by log n, converges almost surely to a constant depending on the source. By definition of the suffix trees, the study of this parameter happens to be a word apparition time issue. We obtain the convergence using results of Abadi and Vergne in this field
Scholler, Rémy. "Analyse de données de signalisation mobile pour l’étude de la mobilité respectueuse de la vie privée : Application au secteur du transport routier de marchandises". Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCD001.
Texto completoMobile network operators have a significant data source derived from communications of all connected objects (not just smartphones) with the network. These signaling data is a massive source of location data and are regularly used for the mobility analysis. However, potential uses face two major challenges: their low spatiotemporal precision and their highly sensitive nature concerning privacy.In the first phase, the thesis work enhances the understanding of the mobility state (stationary or in motion), speed, direction of movement of connected objects, and the route they take on a transportation infrastructure (e.g., road or rail).In the second phase, we demonstrate how to ensure the confidentiality of continuously produced mobility statistics. The use of signaling data, whether related to users or various connected objects, is legally regulated. For the study of mobility, operators tend to publish anonymized statistics (aggregated data). Specifically, the aim is to calculate complex and anonymized mobility statistics "on the fly" using differential privacy methods and probabilistic data structures (such as Bloom filters).Finally, in the third phase, we illustrate the potential of signaling data and the proposed approaches in this manuscript for quasi-real-time calculation of anonymous statistics on road freight transport. However, this is just an example of what could apply to other subjects analyzing population behaviors and activities with significant public and economic policy implications
Boyer, Laurent. "Apprentissage probabiliste de similarités d'édition". Phd thesis, Université Jean Monnet - Saint-Etienne, 2011. http://tel.archives-ouvertes.fr/tel-00718835.
Texto completoJabbour-Hattab, Jean. "Une approche probabiliste du profil des arbres binaires de recherche". Versailles-St Quentin en Yvelines, 2001. http://www.theses.fr/2001VERS002V.
Texto completoBarriot, Roland. "Intégration des connaissances biologiques à l'échelle de la cellule". Bordeaux 1, 2005. http://www.theses.fr/2005BOR13100.
Texto completoMohamed, Hanène. "Etude probabiliste d'algorithmes en arbre". Paris 6, 2007. https://tel.archives-ouvertes.fr/tel-00270742.
Texto completoIn this thesis a general class of tree algorithms is analyzed. It is shown that, by using an appropriate probabilistic representation of the quantities of interest, the asymptotic behavior of these algorithms can be obtained quite easily. This approach gives a unified probabilistic treatment of these questions. It simplifies and extends some of the results known in this domain
Mohamed, Hanene. "Étude Probabiliste d'Algorithmes en Arbre". Phd thesis, Université Pierre et Marie Curie - Paris VI, 2007. http://tel.archives-ouvertes.fr/tel-00270742.
Texto completoReype, 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.
Texto completoThe 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
Libros sobre el tema "Structures de données probabilistes"
Aho, Alfred V. Structures de données et algorithmes. Paris: InterÉditions, 1987.
Buscar texto completoWirth, Niklaus. Algorithmes et structures de données. 2a ed. Paris: Eyrolles, 1989.
Buscar texto completoGuyomard, Marc. Structures de données et méthodes formelles. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8.
Texto completoCarrez, Christian. Des structures aux bases de données. Paris: Dunod, 1990.
Buscar texto completoGuyomard, Marc. Structures de données et méthodes formelles. Paris: Springer Paris, 2011.
Buscar texto completoBoussard, Jean-Claude. Programmation avancée: Algorithmique et structures de données. Paris: Eyrolles, 1987.
Buscar texto completoLipschutz, Seymour. Les structures de données: Cours et problèmes. Auckland: McGraw-Hill, 1987.
Buscar texto completoPichat, Étienne. Ingénierie des données: Systèmes d'information, modèles et bases de données. Paris: Masson, 1990.
Buscar texto completoADA 95: Orientation objet, structures de données et algorithmes. Bruxelles: De Boeck Université, 2000.
Buscar texto completoEfficient structures for geometric data management. Berlin: Springer-Verlag, 1988.
Buscar texto completoCapítulos de libros sobre el tema "Structures de données probabilistes"
Bretto, Alain, Alain Faisant y François Hennecart. "(Di)graphes et structures de données". En Éléments de théorie des graphes, 61–98. Paris: Springer Paris, 2012. http://dx.doi.org/10.1007/978-2-8178-0281-7_3.
Texto completoGuyomard, Marc. "étude de quelques structures outils". En Structures de données et méthodes formelles, 77–105. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_3.
Texto completoGuyomard, Marc. "Mathématiques pour la spécification et les structures de données". En Structures de données et méthodes formelles, 15–57. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_1.
Texto completoGuyomard, Marc. "Tableaux flexibles". En Structures de données et méthodes formelles, 377–99. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_10.
Texto completoGuyomard, Marc. "Spécifications + Fonction d’abstraction + Calcul = Programme". En Structures de données et méthodes formelles, 59–76. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_2.
Texto completoGuyomard, Marc. "Analyse d’algorithmes". En Structures de données et méthodes formelles, 107–28. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_4.
Texto completoGuyomard, Marc. "Exemples". En Structures de données et méthodes formelles, 129–44. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_5.
Texto completoGuyomard, Marc. "Ensembles de clés scalaires". En Structures de données et méthodes formelles, 147–271. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_6.
Texto completoGuyomard, Marc. "Ensembles de clés structurées". En Structures de données et méthodes formelles, 273–311. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_7.
Texto completoGuyomard, Marc. "Files simples". En Structures de données et méthodes formelles, 313–25. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0200-8_8.
Texto completoInformes sobre el tema "Structures de données probabilistes"
Brinkerhoff, Derick W., Sarah Frazer y Lisa McGregor. S'adapter pour apprendre et apprendre pour s'adapter : conseils pratiques tirés de projets de développement internationaux. RTI Press, enero de 2018. http://dx.doi.org/10.3768/rtipress.2018.pb.0015.1801.fr.
Texto completoSnyder, D. B., A. Vaillancourt, B. A. Kjarsgaard, G. Savard y E. A. de Kemp. 3-D mantle structure of the Superior Craton. Natural Resources Canada/CMSS/Information Management, 2024. http://dx.doi.org/10.4095/p8zz9che61.
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