Academic literature on the topic 'Plans d'expérience optimaux (Statistique)'
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Dissertations / Theses on the topic "Plans d'expérience optimaux (Statistique)"
Koné, Mamadou. "Optimalité des plans d'expériences équilibrés pour les périodes." Paris 6, 2011. http://www.theses.fr/2011PA066509.
Full textJoutard, Cyrille. "Grandes déviations en statistique asymptotique." Toulouse 3, 2004. http://www.theses.fr/2004TOU30071.
Full textMahfouz, Mariam. "Plans d'expériences optimaux et compétition entre traitements." Pau, 1988. http://www.theses.fr/1988PAUU3030.
Full textBelouni, Mohamad. "Plans d'expérience optimaux en régression appliquée à la pharmacocinétique." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM056/document.
Full textThe problem of interest is to estimate the concentration curve and the area under the curve (AUC) by estimating the parameters of a linear regression model with autocorrelated error process. We construct a simple linear unbiased estimator of the concentration curve and the AUC. We show that this estimator constructed from a sampling design generated by an appropriate density is asymptotically optimal in the sense that it has exactly the same asymptotic performance as the best linear unbiased estimator (BLUE). Moreover, we prove that the optimal design is robust with respect to a misspecification of the autocovariance function according to a minimax criterion. When repeated observations are available, this estimator is consistent and has an asymptotic normal distribution. All those results are extended to the error process of Hölder with index including between 0 and 2. Finally, for small sample sizes, a simulated annealing algorithm is applied to a pharmacokinetic model with correlated errors
Bousbia-Salah, Ryad. "Optimisation dynamique en temps-réel d’un procédé de polymérisation par greffage." Electronic Thesis or Diss., Université de Lorraine, 2018. http://www.theses.fr/2018LORR0242.
Full textIn a schematic way, process optimization consists of three basic steps: (i) modeling, in which a (phenomenological) model of the process is developed, (ii) problem formulation, in which the criterion of Performance, constraints and decision variables are defined, (iii) the resolution of the optimal problem, in which the optimal profiles of the decision variables are determined. It is important to emphasize that these optimal profiles guarantee the optimality for the model used. When applied to the process, these profiles are optimal only when the model perfectly describes the behavior of the process, which is very rarely the case in practice. Indeed, uncertainties about model parameters, process disturbances, and structural model errors mean that the optimal profiles of the model-based decision variables will probably not be optimal for the process. The objective of this thesis is to develop a conceptual strategy for using experimental measurements online so that the process not only satisfies the necessary conditions, but also the optimal conditions. This conceptual development will in particular be based on recent advances in deterministic optimization (the stochastic methods will not be dealt with in this work) of processes based on the estimation of the state variables that are not measured by a moving horizon observer. A dynamic real-time optimization (D-RTO) methodology has been developed and applied to a batch reactor where polymer grafting reactions take place. The objective is to determine the on-line reactor temperature profile that minimizes the batch time while meeting terminal constraints on the overall conversion rate and grafting efficiency
Yousfi, Elqasyr Khadija. "MODÉLISATION ET ANALYSE STATISTIQUE DES PLANS D'EXPÉRIENCE SÉQUENTIELS." Phd thesis, Université de Rouen, 2008. http://tel.archives-ouvertes.fr/tel-00377114.
Full textTinsson, Walter. "Plans d'expérience à facteurs quantitatifs et à effets de blocs aléatoires." Pau, 1998. http://www.theses.fr/1998PAUU3021.
Full textDruilhet, Pierre. "Optimalités des plans d'expériences équilibrés pour les voisinages." Toulouse 3, 1995. http://www.theses.fr/1995TOU30283.
Full textTlalolini, Romero David. "Génération de mouvements optimaux de marche pour des robots bipèdes 3D." Nantes, 2008. http://www.theses.fr/2008NANT2112.
Full textThis work is devoted to the optimal motions generation of cycle walk for the anthropomorphic bipedal robots walking in the space. These robots are assumed to consist of a kinematics structure which retains only basic human locomotion mobility's on the level of the hip-knee-ankle-foot kinematics chain. The decomposition of the human gaits cycle, robot modelling and the constraints linked to the contact between the foot and the ground are presented. To dene dynamic model and impact model, the method of Newton-Euler is used. The motions generation of walking is posed under the form of a constrained parameter optimization problem. The resolution of this problem is obtained by Sequential Quadratic Programming (SQP) methods. The criterion is optimized in order to increase the autonomy of energy of the biped robot. To achieve and improve the convergence of the optimization algorithm, the gradient analytic calculation of the criteria was performed. In a preliminary study limited of the sagittal plane, dierent gaits are compared. These are dened by instantaneous double support phases or nite time double support phases and the single support phases including or not an under-actuated sub-phase in which stance foot rotates about the stance toe. These results are then generalized to the case of three-dimensional walk. The comparison of two gaits which includes the impacts and the single support phases with or without rolling of the foot is achieved. One can saw from these dierent studies that the introduction of phase of foot rolling in a single support phase allows much higher walking velocity with less energy consumption
Bousbia-Salah, Ryad. "Optimisation dynamique en temps-réel d’un procédé de polymérisation par greffage." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0242/document.
Full textIn a schematic way, process optimization consists of three basic steps: (i) modeling, in which a (phenomenological) model of the process is developed, (ii) problem formulation, in which the criterion of Performance, constraints and decision variables are defined, (iii) the resolution of the optimal problem, in which the optimal profiles of the decision variables are determined. It is important to emphasize that these optimal profiles guarantee the optimality for the model used. When applied to the process, these profiles are optimal only when the model perfectly describes the behavior of the process, which is very rarely the case in practice. Indeed, uncertainties about model parameters, process disturbances, and structural model errors mean that the optimal profiles of the model-based decision variables will probably not be optimal for the process. The objective of this thesis is to develop a conceptual strategy for using experimental measurements online so that the process not only satisfies the necessary conditions, but also the optimal conditions. This conceptual development will in particular be based on recent advances in deterministic optimization (the stochastic methods will not be dealt with in this work) of processes based on the estimation of the state variables that are not measured by a moving horizon observer. A dynamic real-time optimization (D-RTO) methodology has been developed and applied to a batch reactor where polymer grafting reactions take place. The objective is to determine the on-line reactor temperature profile that minimizes the batch time while meeting terminal constraints on the overall conversion rate and grafting efficiency
Books on the topic "Plans d'expérience optimaux (Statistique)"
W, Neustadt Lucien, ed. The mathematical theory of optimal processes. New York: Gordon and Breach Science Publishers, 1986.
Find full text1945-, Park Sung H., and Vining G. Geoffrey 1954-, eds. Statistical process monitoring and optimization. New York: Marcel Dekker, 2000.
Find full textSequential Analysis and Optimal Design (CBMS-NSF Regional Conference Series in Applied Mathematics) (CBMS-NSF Regional Conference Series in Applied Mathematics). 2nd ed. Society for Industrial Mathematics, 1987.
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