Littérature scientifique sur le sujet « Inversions statistiques »
Créez une référence correcte selon les styles APA, MLA, Chicago, Harvard et plusieurs autres
Sommaire
Consultez les listes thématiques d’articles de revues, de livres, de thèses, de rapports de conférences et d’autres sources académiques sur le sujet « Inversions statistiques ».
À côté de chaque source dans la liste de références il y a un bouton « Ajouter à la bibliographie ». Cliquez sur ce bouton, et nous générerons automatiquement la référence bibliographique pour la source choisie selon votre style de citation préféré : APA, MLA, Harvard, Vancouver, Chicago, etc.
Vous pouvez aussi télécharger le texte intégral de la publication scolaire au format pdf et consulter son résumé en ligne lorsque ces informations sont inclues dans les métadonnées.
Articles de revues sur le sujet "Inversions statistiques"
Crétat, Julien, Yves Richard, Olivier Planchon, Justin Emery, Melissa Poupelin, Mario Rega, Julien Pergaud et al. « Impact de la topographie et de la circulation atmosphérique sur l’îlot de chaleur urbain en situation de canicule (Dijon, France) ». Climatologie 20 (2023) : 10. http://dx.doi.org/10.1051/climat/202320010.
Texte intégralUrquijo, Laura Gómez. « La conexión entre política de cohesión y gobernanza económica en la UE : Eficiencia del nuevo marco para abordar las consecuencias de la crisis ». Regions and Cohesions 5, no 3 (1 décembre 2015) : 44–62. http://dx.doi.org/10.3167/reco.2015.050304.
Texte intégralFesty, Patrick. « Principes et pratique des perspectives démographiques : six sujets corrigés ». Population Vol. 46, no 6 (1 juin 1991) : 1689–710. http://dx.doi.org/10.3917/popu.p1991.46n6.1710.
Texte intégralCho, Soojin, et Kyoungsuk Park. « Alignments, crossings, cycles, inversions, and weak Bruhat order in permutation tableaux of type $B$ ». Discrete Mathematics & ; Theoretical Computer Science DMTCS Proceedings, 27th..., Proceedings (1 janvier 2015). http://dx.doi.org/10.46298/dmtcs.2484.
Texte intégralCorteel, Sylvie, et Sandrine Dasse-Hartaut. « Statistics on staircase tableaux, eulerian and mahonian statistics ». Discrete Mathematics & ; Theoretical Computer Science DMTCS Proceedings vol. AO,..., Proceedings (1 janvier 2011). http://dx.doi.org/10.46298/dmtcs.2907.
Texte intégralKim, Jang Soo, Karola Mészáros, Greta Panova et David B. Wilson. « Dyck tilings, linear extensions, descents, and inversions ». Discrete Mathematics & ; Theoretical Computer Science DMTCS Proceedings vol. AR,..., Proceedings (1 janvier 2012). http://dx.doi.org/10.46298/dmtcs.3081.
Texte intégralHicks, Angela, et Yeonkyung Kim. « An explicit formula for ndinv, a new statistic for two-shuffle parking functions ». Discrete Mathematics & ; Theoretical Computer Science DMTCS Proceedings vol. AR,..., Proceedings (1 janvier 2012). http://dx.doi.org/10.46298/dmtcs.3027.
Texte intégralKollie, James L. S. « EFFECTS OF INCOME DIVERSIFICATION ON FINANCIAL PERFORMANCE OF COMMERCIAL BANKS LISTED IN SIERRA LEONE ». European Journal of Management and Marketing Studies 9, no 1 (7 mai 2024). http://dx.doi.org/10.46827/ejmms.v9i1.1702.
Texte intégralThèses sur le sujet "Inversions statistiques"
Boucher, Eulalie. « Designing Deep-Learning models for surface and atmospheric retrievals from the IASI infrared sounder ». Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS145.
Texte intégralObserving the Earth is vital to comprehend and monitor the complex behaviour of our planet. Satellites, equipped with a number of sophisticated sensors, serve as a key platform for this, offering an opportunity to observe the Earth globally and continuously. Machine Learning (ML) techniques have been used in the remote sensing community for several decades to deal with the vast amount of data generated daily by Earth observation systems. The revolution brought about by novel Deep Learning (DL) techniques has however opened up new possibilities for the exploitation of satellite observations. This research aims to show that image-processing techniques such as Convolutional Neural Networks (CNNs), provided that they are well mastered, have the potential to improve the estimation of the Earth's atmospheric and surface parameters. By looking at the observations at the image scale rather than at the pixel scale, spatial dependencies can be taken into account. Such techniques will be used for the retrieval of surface and atmospheric temperatures, as well as cloud detection and classification from the Infrared Atmospheric Sounding Interferometer (IASI) observations. IASI, onboard the polar orbiting satellites Metop, is a hyperspectral sounder gathering data across a broad range of infrared wavelengths that are suitable to identify atmospheric constituents for a range of atmospheric vertical levels, as well as surface parameters. In addition to improving the quality of the retrievals, such Artificial Intelligence (AI) methods are capable of dealing with images that contain missing data, better estimating extreme events (often overlooked by traditional ML techniques) and estimating retrieval uncertainties. This thesis shows why AI methods should be the preferred approach for the exploitation of observations coming from new satellite missions such as IASI-NG or MTG-S IRS
Smith, Pascalle. « Modélisation des cultures européennes au sein de la biosphère : phénologie, productivité et flux de CO2 ». Paris 6, 2008. http://www.theses.fr/2008PA066250.
Texte intégralCamps, Pierre. « Comportement du champ magnétique de la terre au cours de ses renversements : étude d'un exemple, variations ultra rapides et caractéristiques statistiques globales ». Montpellier 2, 1994. http://www.theses.fr/1994MON20203.
Texte intégralNier, Vincent Philippe. « Estimation statistique des propriétés physiques de monocouches cellulaires ». Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066233/document.
Texte intégralEpithelial cells are known to form cohesive monolayers, a form of tissue organization encountered in the lung, the kidney or the skin. From in vitro experiments, we have characterized the mechanical properties of cell monolayers. We have studied the closure of circular wounds over a nonadhesive substrate. Comparing different models, we have shown how closure is possible thanks to a contractile acto-myosin cable and to fluctuations of the tissue tension. Traction Force Microscopy (TFM) allows to measure the forces that cells exert on their substrate. Starting from this measurement and using the force balance equations, we have solved this underdetermined problem by Bayesian inversion and obtained the internal stress field of the tissue. Applying this method on single images (BISM: Bayesian Inversion Stress Microscopy), and adapting it with a Kalman filter for movies (KISM: Kalman Inversion Stress Microscopy) we have inferred the stress tensor of cell monolayers, without making any hypothesis on the tissue rheology. Finally, we have estimated the stresses directly from the substrate displacements, without computing the traction forces and thus reducing the number of matrix inversions (BISMu: Bayesian Inversion Stress Microscopy from substrate displacements)
Arnst, Maarten. « Inversion of probabilistic models of structures using measured transfer functions ». Châtenay-Malabry, Ecole centrale de Paris, 2007. http://www.theses.fr/2007ECAP1037.
Texte intégralThe aim of this thesis is to develop a methodology for the experimental identification of probabilistic models for the dynamical behaviour of structures. The inversion of probabilistic structural models with minimal parameterization, introduced by Soize, from measured transfer functions is in particular considered. It is first shown that the classical methods of estimation from the theory of mathematical statistics, such as the method of maximum likelihood, are not well-adapted to formulate and solve this inverse problem. In particular, numerical difficulties and conceptual problems due to model misspecification are shown to prohibit the application of the classical methods. The inversion of probabilistic structural models is then formulated alternatively as the minimization, with respect to the parameters to be identified, of an objective function measuring a distance between the experimental data and the probabilistic model. Two principles of construction for the definition of this distance are proposed, based on either the loglikelihood function, or the relative entropy. The limitation of the distance to low-order marginal laws is demonstrated to allow to circumvent the aforementioned difficulties. The methodology is applied to examples featuring simulated data and to a civil and environmental engineering case history featuring real experimental data
Ars, Sébastien. « Caractérisation des émissions de méthane à l'échelle locale à l'aide d'une méthode d'inversion statistique basée sur un modèle gaussien paramétré avec les données d'un gaz traceur ». Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLV030/document.
Texte intégralThe increase of atmospheric methane concentrations since the beginning of the industrial era is directly linked to anthropogenic activities. This increase is partly responsible for the enhancement of the greenhouse effect leading to a rise of Earth's surface temperatures and a degradation of air quality. There are still considerable uncertainties regarding methane emissions estimates from many sources at local scale. A better characterization of these sources would help the implementation of effective adaptation and mitigation policies to reduce these emissions.To do so, we have developed a new method to quantify methane emissions from local sites based on the combination of mobile atmospheric measurements, a Gaussian model and a statistical inversion. These atmospheric measurements are carried out within the framework of the tracer method, which consists in emitting a gas co-located with the methane source at a known flow. An estimate of methane emissions can be given by measuring the tracer and methane concentrations through the emission plume coming from the site. This method presents some limitations especially when several sources and/or extended sources can be found on the studied site. In these conditions, the colocation of the tracer and methane sources is difficult. The Gaussian model enables to take into account this bad collocation. It also gives a separate estimate of each source of a site when the classical tracer release method only gives an estimate of its total emissions. The statistical inversion enables to take into account the uncertainties associated with the model and the measurements.The method is based on the use of the measured tracer gas concentrations to choose the stability class of the Gaussian model that best represents the atmospheric conditions during the measurements. These tracer data are also used to parameterize the error associated with the measurements and the model in the statistical inversion. We first tested this new method with controlled emissions of tracer and methane. The tracer and methane sources were positioned in different configurations in order to better understand the contributions of this method compared to the traditional tracer method. These tests have demonstrated that the statistical inversion parameterized by the tracer gas data gives better estimates of methane emissions when the tracer and methane sources are not perfectly collocated or when there are several sources of methane.In a second time, I applied this method to two sites known for their methane emissions, namely a farm and a gas distribution facility. These measurements enabled us to test the applicability and robustness of the method under more complex methane source distribution conditions and gave us better estimates of the total methane emissions of these sites that take into account the location of the tracer regarding methane sources. Separate estimates of every source within the site are highly dependent on the meteorological conditions during the measurements. The analysis of the correlations on the posterior uncertainties between the different sources gives a diagnostic of the separability of the sources.Finally I focused on methane emissions associated with the waste sector. To do so, I carried out several measurement campaigns in landfills and wastewater treatment plants and I also used data collected on this type of sites during other projects. I selected the most suitable method to estimate methane emissions of each site and the obtained estimates for each one of these sites show the variability of methane emissions in the waste sector
Romary, Thomas. « Inversion des modèles stochastiques de milieux hétérogènes ». Paris 6, 2008. https://tel.archives-ouvertes.fr/tel-00395528.
Texte intégralArs, Sébastien. « Caractérisation des émissions de méthane à l'échelle locale à l'aide d'une méthode d'inversion statistique basée sur un modèle gaussien paramétré avec les données d'un gaz traceur ». Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLV030.
Texte intégralThe increase of atmospheric methane concentrations since the beginning of the industrial era is directly linked to anthropogenic activities. This increase is partly responsible for the enhancement of the greenhouse effect leading to a rise of Earth's surface temperatures and a degradation of air quality. There are still considerable uncertainties regarding methane emissions estimates from many sources at local scale. A better characterization of these sources would help the implementation of effective adaptation and mitigation policies to reduce these emissions.To do so, we have developed a new method to quantify methane emissions from local sites based on the combination of mobile atmospheric measurements, a Gaussian model and a statistical inversion. These atmospheric measurements are carried out within the framework of the tracer method, which consists in emitting a gas co-located with the methane source at a known flow. An estimate of methane emissions can be given by measuring the tracer and methane concentrations through the emission plume coming from the site. This method presents some limitations especially when several sources and/or extended sources can be found on the studied site. In these conditions, the colocation of the tracer and methane sources is difficult. The Gaussian model enables to take into account this bad collocation. It also gives a separate estimate of each source of a site when the classical tracer release method only gives an estimate of its total emissions. The statistical inversion enables to take into account the uncertainties associated with the model and the measurements.The method is based on the use of the measured tracer gas concentrations to choose the stability class of the Gaussian model that best represents the atmospheric conditions during the measurements. These tracer data are also used to parameterize the error associated with the measurements and the model in the statistical inversion. We first tested this new method with controlled emissions of tracer and methane. The tracer and methane sources were positioned in different configurations in order to better understand the contributions of this method compared to the traditional tracer method. These tests have demonstrated that the statistical inversion parameterized by the tracer gas data gives better estimates of methane emissions when the tracer and methane sources are not perfectly collocated or when there are several sources of methane.In a second time, I applied this method to two sites known for their methane emissions, namely a farm and a gas distribution facility. These measurements enabled us to test the applicability and robustness of the method under more complex methane source distribution conditions and gave us better estimates of the total methane emissions of these sites that take into account the location of the tracer regarding methane sources. Separate estimates of every source within the site are highly dependent on the meteorological conditions during the measurements. The analysis of the correlations on the posterior uncertainties between the different sources gives a diagnostic of the separability of the sources.Finally I focused on methane emissions associated with the waste sector. To do so, I carried out several measurement campaigns in landfills and wastewater treatment plants and I also used data collected on this type of sites during other projects. I selected the most suitable method to estimate methane emissions of each site and the obtained estimates for each one of these sites show the variability of methane emissions in the waste sector
Romary, Thomas. « INVERSION DES MODELES STOCHASTIQUES DE MILIEUX HETEROGENES ». Phd thesis, Université Pierre et Marie Curie - Paris VI, 2008. http://tel.archives-ouvertes.fr/tel-00395528.
Texte intégralHan, Bin. « Gamma positivity in enumerative combinatorics ». Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1115/document.
Texte intégralThe gamma positivity of a combinatorial sequence unifies both unimodality and symmetry. Finding new family of objets whose enumerative sequences have gamma positivity is a challenge and important topic in recent years. it has received considerable attention in recent times because of Gal’s conjecture, which asserts that the gamma-vector has nonnegative entries for any flag simple polytope. Often times, the h-polynomial for simplicial polytopes of combinatorial signification can be given as a generating function over a related set of combinatorial objects with respect to some statistic like the descent numbers, whose enumerative polynomials on permutations are Eulerian polynomials.This work deals with the gamma properties of several enumerative polynomials of permutation such as Eulerian polynomials and Narayana polynomials. This thesis contains five chapters