Academic literature on the topic 'Méthodes Agnostiques aux Modèles'
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Journal articles on the topic "Méthodes Agnostiques aux Modèles":
Monfort, Alain. "Quelques développements récents des méthodes macroéconométriques." L'Actualité économique 68, no. 1-2 (March 10, 2009): 305–24. http://dx.doi.org/10.7202/602069ar.
Battista, Katelyn, Liqun Diao, Karen A. Patte, Joel A. Dubin, and Scott T. Leatherdale. "Utilisation des arbres décisionnels dans la recherche en surveillance de la santé de la population : application aux données d’enquête sur la santé mentale des jeunes de l’étude COMPASS." Promotion de la santé et prévention des maladies chroniques au Canada 43, no. 2 (February 2023): 78–92. http://dx.doi.org/10.24095/hpcdp.43.2.03f.
Test, Mary Ann. "Modèles de traitement dans la communauté pour adultes ayant des maladies mentales graves et persistantes." Dossier : Le suivi communautaire 23, no. 2 (September 11, 2007): 119–47. http://dx.doi.org/10.7202/032456ar.
Jellad, Asma. "Identification des propriétés élastoplastiques des films minces de CrN en utilisant la technique de nanoindentation et la modélisation par éléments finis (FEM)." Matériaux & Techniques 111, no. 4 (2023): 403. http://dx.doi.org/10.1051/mattech/2023029.
Regniers, Olivier, Lionel Bombrun, and Christian Germain. "Modélisation de texture basée sur les ondelettes pour la détection de parcelles viticoles à partir d'images Pléiades panchromatiques." Revue Française de Photogrammétrie et de Télédétection, no. 208 (September 8, 2014): 117–22. http://dx.doi.org/10.52638/rfpt.2014.122.
Bultez, Alain. "Econométrie de la compétitivité: modèles et contre-exemples." Recherche et Applications en Marketing (French Edition) 12, no. 1 (March 1997): 21–44. http://dx.doi.org/10.1177/076737019701200102.
Mandrillon, Marie-Hélène. "Les Voies du Politique en URSS : L'Exemple de L'Écologie." Annales. Histoire, Sciences Sociales 46, no. 6 (December 1991): 1375–88. http://dx.doi.org/10.3406/ahess.1991.279014.
Ado, Issa, and Adel Boughrara. "Modélisations prospective et rétrospective : comparaison et applications." Économie appliquée 49, no. 4 (1996): 61–91. http://dx.doi.org/10.3406/ecoap.1996.1616.
Temple, Ludovic, Ariane Gaunand, Gilles Trouche, and Eric Vall. "Évaluer les impacts des recherches en agriculture sur la société et les écosystèmes : outils, méthodes, études de cas." Cahiers Agricultures 27, no. 3 (May 2018): 34002. http://dx.doi.org/10.1051/cagri/2018022.
Ouarda, T. B. M. J., M. Lang, B. Bobée, J. Bernier, and P. Bois. "Synthèse de modèles régionaux d'estimation de crue utilisée en France et au Québec." Revue des sciences de l'eau 12, no. 1 (April 12, 2005): 155–82. http://dx.doi.org/10.7202/705347ar.
Dissertations / Theses on the topic "Méthodes Agnostiques aux Modèles":
Danesh, Alaghehband Tina Sadat. "Vers une conception robuste en ingénierie des procédés. Utilisation de modèles agnostiques de l'interprétabilité en apprentissage automatique." Electronic Thesis or Diss., Toulouse, INPT, 2023. http://www.theses.fr/2023INPT0138.
Robust process design holds paramount importance in various industries, such as process and chemical engineering. The nature of robustness lies in ensuring that a process can consistently deliver desired outcomes for decision-makers and/or stakeholders, even when faced with intrinsic variability and uncertainty. A robustly designed process not only enhances product quality and reliability but also significantly reduces the risk of costly failures, downtime, and product recalls. It enhances efficiency and sustainability by minimizing process deviations and failures. There are different methods to approach the robustness of a complex system, such as the design of experiments, robust optimization, and response surface methodology. Among the robust design methods, sensitivity analysis could be applied as a supportive technique to gain insights into how changes in input parameters affect performance and robustness. Due to the rapid development and advancement of engineering science, the use of physical models for sensitivity analysis presents several challenges, such as unsatisfied assumptions and computation time. These problems lead us to consider applying machine learning (ML) models to complex processes. Although, the issue of interpretability in ML has gained increasing importance, there is a growing need to understand how these models arrive at their predictions or decisions and how different parameters are related. As their performance consistently surpasses that of other models, such as knowledge-based models, the provision of explanations, justifications, and insights into the workings of ML models not only enhances their trustworthiness and fairness but also empowers stakeholders to make informed decisions, identify biases, detect errors, and improve the overall performance and reliability of the process. Various methods are available to address interpretability, including model-specific and model-agnostic methods. In this thesis, our objective is to enhance the interpretability of various ML methods while maintaining a balance between accuracy and interpretability to ensure decision-makers or stakeholders that our model or process could be considered robust. Simultaneously, we aim to demonstrate that users can trust ML model predictions guaranteed by model-agnostic techniques, which work across various scenarios, including equation-based, hybrid, and data-driven models. To achieve this goal, we applied several model-agnostic methods, such as partial dependence plots, individual conditional expectations, accumulated local effects, etc., to diverse applications
Grazian, Clara. "Contributions aux méthodes bayésiennes approchées pour modèles complexes." Thesis, Paris Sciences et Lettres (ComUE), 2016. http://www.theses.fr/2016PSLED001.
Recently, the great complexity of modern applications, for instance in genetics,computer science, finance, climatic science etc., has led to the proposal of newmodels which may realistically describe the reality. In these cases, classical MCMCmethods fail to approximate the posterior distribution, because they are too slow toinvestigate the full parameter space. New algorithms have been proposed to handlethese situations, where the likelihood function is unavailable. We will investigatemany features of complex models: how to eliminate the nuisance parameters fromthe analysis and make inference on key quantities of interest, both in a Bayesianand not Bayesian setting, and how to build a reference prior
Tarhini, Ali. "Analyse numérique des méthodes quasi-Monte Carlo appliquées aux modèles d'agglomération." Chambéry, 2008. http://www.theses.fr/2008CHAMS015.
Monte Carlo (MC) methods are probabilistic methods based on the use of random numbers in repeated experiments. Quasi-Monte Carlo (QMC) methods are deterministic versions of Monte Carlo methods. Random sequences are replaced by low discrepancy sequences. These sequences ha ve a better uniform repartition in the s-dimensional unit cube. We use a special class of low discrepany sequences called (t,s)-sequences. In this work, we develop and analyze Monte Carlo and quasi-Monte Carlo particle methods for agglomeration phenomena. We are interested, in particular, in the numerical simulation of the discrete coagulation equations (the Smoluchowski equation), the continuous coagulation equation, the continuous coagulation-fragmentation equation and the general dynamics equation (GDE) for aerosols. In all these particle methods, we write the equation verified by the mass distribution density and we approach this density by a sum of n Dirac measures ; these measures are weighted when simulating the GDE equation. We use an explicit Euler disretiza tion scheme in time. For the simulation of coagulation and coagulation-fragmentation, the numerical particles evolves by using random numbers (for MC simulations) or by quasi-Monte Carlo quadratures. To insure the convergence of the numerical scheme, we reorder the numerical particles by their increasing mass at each time step. In the case of the GDE equation, we use a fractional step iteration scheme : coagulation is simulated as previously, other phenomena (like condensation, evaporation and deposition) are integrated by using a deterministic particle method for solving hyperbolic partial differential equation. We prove the convergence of the QMC numerical scheme in the case of the coagulation equation and the coagulation-fragmentation equation, when the number n of numerical particles goes to infinity. All our numerical tests show that the numerical solutions calculated by QMC algorithms converges to the exact solutions and gives better results than those obtained by the corresponding Monte Carlo strategies
Rakotomarolahy, Patrick. "Méthodes non paramétriques : estimation, analyse et applications aux cycles économiques." Paris 1, 2011. http://www.theses.fr/2011PA010045.
Castric, Sébastien. "Méthodes de recalage de modèles et application aux émissions des moteurs diesel." Compiègne, 2007. http://www.theses.fr/2007COMP1696.
Since some decades, European vehicles are subjected to normative laws about pollutant emissions. To face these constraints, car manufacturers have used more and more complex technologies especially for diesel engine cars. This situation has led to a complexification of engine tuning since the numbers of setting parameters has increased too. The present research work was made for the car manufacturer Renault SAS. It aims at proposing methods that allow readjusting models and applications over pollutant models of diesel engine. Renault decided to use techniques of design of experiments, modelling and optimization to solve the problem of diesel engine tuning for emissions. Even if this approach gave good results, it has some drawbacks. The tuning process is composed of loops. Each loop involves hardware changes in the engine. In this case, the model representing the engine’s behaviour, which is a LOLIMOT model, is not valid anymore. Considering that it is not possible to completely rebuild a model, a question appears: “How is it possible to readjust the model after an hardware change by doing as few tests as possible?” This PhD proposes some ways to solve this problem. The first one consists in using the bayesian theory. By using the initial model as an a priori, we created an algorithm permitting to readjust LOLIMOT models. In addition, we proposed a method derived from the first one, and, which aims at using the tuner knowledge about the engine as a prior knowledge. We tested our methods by simulation and owing to tests made on a 2L diesel engine, which was subjected to different hardware changes. In a second time, we considered that even if the Bayesian theory is able to take into account some knowledge, it does not take into account the hardware change characteristics. Thus, we decided to create a new model integrating physical parameters, like, for example, the number of holes in the injectors. We developed a model of diesel combustion. It simulates the evolution of thermodynamic variables inside the combustion chamber even for the multi injection case. Next, we adapted models of pollutants using these variables as inputs. We tested the whole model on prediction of cylinder pressure and pollutants over 2L diesel engine tests
Darblade, Gilles. "Méthodes numériques et conditions aux limites pour les modèles Shallow-Water multicouches." Bordeaux 1, 1997. http://www.theses.fr/1997BOR10588.
Debreu, Laurent. "Raffinement adaptatif de maillage et méthodes de zoom : application aux modèles d'océan." Université Joseph Fourier (Grenoble), 2000. http://www.theses.fr/2000GRE10004.
Montier, Laurent. "Application de méthodes de réduction de modèles aux problèmes d'électromagnétisme basse fréquence." Thesis, Paris, ENSAM, 2018. http://www.theses.fr/2018ENAM0029/document.
In the electrical engineering field, numerical simulation allows to avoid experiments which can be expensive, difficult to carry out or harmful for the device. In this context, the Finite Element Method has become to be one of the most used approach since it allows to obtain precise results on devices with complex geometries. However, these simulations can be computationally expensive because of a large number of unknowns and time-steps, and of strong nonlinearities of ferromagnetic materials to take into account. Numerical techniques to reduce the computational effort are thus needed. In this context, model order reduction approaches seem well adapted to this kind of problem since they have already been successfully applied to many engineering fields, among others, fluid and solid mechanics. A first class of methods allows to seek the solution in a reduced basis, allowing to dramatically reduce the number of unknowns of the numerical model. The most famous technics are probably the Proper Orthogonal Decomposition, the Proper Generalized Decomposition and the Arnoldi Projection. The second class of approaches consists of methods allowing to reduce the computational cost associated to nonlinearities, using interpolation methods like the Empirical Interpolation Method and the Gappy POD. This Ph.D. has been done within the LAMEL, the joint laboratory between the L2EP and EDF R&D, in order to identify and implement the model order reduction methods which are the most adapted to electrical engineering models. These methods are expected to reduce the computational cost while taking into account the motion of an electrical machine rotor, the nonlinearities of the ferromagnetic materials and also the mechanical and electrical environment of the device. Finally, an error indicator which evaluates the error introduced by the reduction technic has been developed, in order to guarantee the accuracy of the results obtained with the reduced model
Infante, Acevedo José Arturo. "Méthodes et modèles numériques appliqués aux risques du marché et à l'évaluation financière." Phd thesis, Université Paris-Est, 2013. http://tel.archives-ouvertes.fr/tel-00937131.
Baskind, Alexis. "Modèles et méthodes de description spatiale de scènes sonores : application aux enregistrements binauraux." Paris 6, 2003. http://www.theses.fr/2003PA066407.
Books on the topic "Méthodes Agnostiques aux Modèles":
St-Pierre, Armand. Méthodes analytiques appliquées aux problèmes de gestion. Saint-Jean-sur-Richelieu, Qué: Éditions Bo-pré, 1986.
Bertrand, Richard. Mode les de mesure: L'apport de la the orie des re ponses aux items. Sainte-Foy [Que.]: Presses de l'Universite du Que bec, 2004.
L, Nering Michael, and Ostini Remo, eds. Handbook of polytomous item response theory models. New York: Routledge, 2010.
Ostini, Remo, and Michael L. Nering. Handbook of Polytomous Item Response Theory Models. Taylor & Francis Group, 2011.
Ostini, Remo, and Michael L. Nering. Handbook of Polytomous Item Response Theory Models. Taylor & Francis Group, 2011.
Ostini, Remo, and Michael L. Nering. Handbook of Polytomous Item Response Theory Models. Routledge, 2011.
Book chapters on the topic "Méthodes Agnostiques aux Modèles":
PONTY, Yann, and Vladimir REINHARZ. "Repliement de l’ARN." In Des séquences aux graphes, 187–229. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9066.ch6.
SIGRIST, Jean-François. "Méthodes « basses fréquences » en vibroacoustique des navires." In Interactions fluide-structure, 39–59. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9078.ch2.
YASTREBOV, Vladislav A. "Méthodes numériques en contact micromécanique." In Modélisation numérique en mécanique fortement non linéaire, 87–145. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9081.ch3.
SANMARTÍN, Isabel. "Approches analytiques en biogéographie : progrès et défis." In La biogéographie, 37–69. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9060.ch2.
SIMANI, Silvio. "Méthodes guidées par les données pour le diagnostic de défauts." In Diagnostic et commande à tolérance de fautes 1, 167–233. ISTE Group, 2024. http://dx.doi.org/10.51926/iste.9058.ch5.
BEN-AHMED, Sabrina, Jean-Noël ALBERTINI, Jean-Pierre FAVRE, C. Alberto FIGUEROA, Eugenio ROSSET, Francesca CONDEMI, and Stéphane AVRIL. "Simulations numériques de l’impact hémodynamique des interventions endovasculaires complexes." In Écoulements biologiques dans les grands vaisseaux, 45–70. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9065.ch2.
CRIQUI, Patrick, Rodica LOISEL, and Lionel LEMIALE. "Scénarios prospectifs à l’horizon 2050." In Économie de l’énergie nucléaire 2, 175–236. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9095.ch5.
DIMITROV, Boyan. "Distributions et processus aléatoires liés aux modèles de files d’attente et de fiabilité." In Théorie des files d’attente 2, 91–147. ISTE Group, 2021. http://dx.doi.org/10.51926/iste.9004.ch3.
Aebi, Carol. "Recherches sur la Sustainability." In Recherches sur la Sustainability, 295–309. EMS Editions, 2023. http://dx.doi.org/10.3917/ems.cheva.2023.01.0295.
Conference papers on the topic "Méthodes Agnostiques aux Modèles":
Hadj SaÏd, M., F. Campana, U. Ordioni, R. Lan, and C. M. Chossegros. "Tendances saisonnières des alvéolites et cellulites de la face en France : données du moteur de recherche Google Trends©." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206603001.
Fontanille, Jacques. "La sémiotique est-elle un art ? Le faire sémiotique comme « art libéral »." In Arts du faire : production et expertise. Limoges: Université de Limoges, 2009. http://dx.doi.org/10.25965/as.3343.
Bernonville, Stéphanie, and Marie-Catherine Beuscart-Zéphir. "Mise en œuvre d'un système d'aide aux choix des méthodes et modèles du GL et de I'IHM dans le cadre de projets visant I'informatisation de processus complexes en milieu hospitalier." In the 20th International Conference of the Association Francophone d'Interaction Homme-Machine. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1512714.1512743.
Reports on the topic "Méthodes Agnostiques aux Modèles":
Marsden, Eric. Partage des modèles de sécurité entre donneurs d’ordres et entreprises intervenantes. Fondation pour une culture de sécurité industrielle, December 2018. http://dx.doi.org/10.57071/360upb.