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Literatura académica sobre el tema "Modèle continu à énergie aléatoire"
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Artículos de revistas sobre el tema "Modèle continu à énergie aléatoire"
Bourass, Mohamed y Mohammed Bouachrine. "Étude structurale des systèmes dissymétriques de structure D-π-A à base de thiénopyrazine destinés aux cellules solaires organiques de type « bulk heterojunction » (BHJ)". Canadian Journal of Chemistry 97, n.º 10 (octubre de 2019): 745–55. http://dx.doi.org/10.1139/cjc-2019-0053.
Texto completoStumpf, André, Emmanuel Augereau, Julien Bonnier, Christophe Delacourt y Eric Delcher. "Mesure des débits par photogrammétrie adaptée aux rivières torrentielles". La Houille Blanche, n.º 5-6 (octubre de 2018): 66–74. http://dx.doi.org/10.1051/lhb/2018053.
Texto completoTesis sobre el tema "Modèle continu à énergie aléatoire"
Ho, Fu-Hsuan. "Aspects algorithmiques du modèle continu à énergie aléatoire". Electronic Thesis or Diss., Toulouse 3, 2023. http://www.theses.fr/2023TOU30184.
Texto completoThis thesis explores the algorithmic perspectives of the branching random walk and the continuous random energy model (CREM). Namely, we are interested in constructing polynomial-time algorithms that can sample the model's Gibbs measure with high probability, and to indentify the hardness regime, which consists of any inverse temperature bêta such that such polynomial-time algorithms do not exist. In Chapter 1, we provide a historical overview of the models and motivate the algorithmic problems under investigation. We also provide an overview on the mean-field spin glasses that motivates the line of our research. In Chapter 2, we address the sampling problem of the Gibbs measure in the context of branching random walk. We identify a critical inverse temperature bêta_c, identical to the static critical point, that the a hardness transition occurs. In the subcritical regime bêta < bêta_c, we establish a recursive sampling algorithm is able to sample the Gibbs measure efficiently. In the supercritical regime bêta > bêta_c,we show that we cannot find polynomial-time algorithm that belongs to a certain class of algorithms. In Chapter 3, we turn our attention to the same sampling problem for the con¬tinuous random energy model (CREM). For the case where the covariance function of this model is concave, we show that for any inverse temperature bêta < to infinity, the recursive sampling algorithm considered in Chapter 2 is able to sample the Gibbs measure efficiently. For the non-concave case, we identify a critical point bêta_G that similar hardness transition as the one in Chapter 2 occurs. We also provide a lower bound of the CREM free energy that might be of independent interest. In Chapter 4, we study the negative moment of the CREM partition function. While this is not connected directly to the main theme of the thesis, it spins off during the course of research. In Chapter 5, we provide an outlook of some further directions that might be interesting to investigate
Pham, Thanh Hung. "Commande optimale sous contraintes pour micro-réseaux en courant continu". Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAT086/document.
Texto completoThe goals of this thesis is to propose modelling and control solutions for the optimal energy management of a DC microgrid under constraints. The studied microgrid system includes electrical storage units (e.g., batteries, supercapacitors), renewable sources (e.g., solar panels) and loads (e.g., an electro-mechanical elevator system). These interconnected components are linked to a three phase electrical grid through a DC bus and associated DC/AC converters. The optimal energy management is usually formulated as an optimal control problem which takes into account the system dynamics, cost, constraints and reference profiles.An optimal energy management for the microgrid is challenging with respect to classical control theories. Needless to say, a DC microgrid is a complex system due to its heterogeneity, distributed nature (both spatial and in sampling time), nonlinearity of dynamics, multi-physic characteristics, the presence of constraints and uncertainties. Moreover, the power-preserving structure and the energy conservation of a microgrid are essential for ensuring a reliable operation.This challenges are tackled through the combined use of port-Hamiltonian formulations, differential flatness, and economic Model Predictive Control.The Port-Hamiltonian formalism allows to explicitly describe the power-preserving structure and the energy conservation of the microgrid and to connect different components of different physical natures through the same formalism. The strongly non-linear system is then translated into a flat representation. Taking into account differential flatness properties, reference profiles are generated such that the dissipated energy and various physical constraints are taken into account. Lastly, we minimize the purchasing/selling electricity cost within the microgrid using the economic Model Predictive Control with the Port-Hamiltonian formalism on graphs.The proposed control designs are validated through simulation results
Vermet, Franck. "Étude asymptotique d'un réseau neuronal: le modèle de mémoire associative de Hopfield". Phd thesis, Université Rennes 1, 1994. http://tel.archives-ouvertes.fr/tel-00598243.
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