Literatura científica selecionada sobre o tema "Prédiction temporelle"
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Artigos de revistas sobre o assunto "Prédiction temporelle"
Yao, Marcel Konan, Djedro Clément Akmel, Kouamé Lazare Akpetou, Albert Trokourey, Kouassi Benjamin Yao e Nogbou Emmanuel Assidjo. "Modélisation de l'évolution spatiotemporelle du phosphore minéral dans une baie lagunaire hypereutrophe tropicale : la baie lagunaire de Tiagba (Côte d'Ivoire)". Revue des sciences de l’eau 30, n.º 3 (28 de março de 2018): 247–58. http://dx.doi.org/10.7202/1044250ar.
Texto completo da fonteGalam, Serge. "Prédire les événements sociaux imprévisibles ?" Intellectica. Revue de l'Association pour la Recherche Cognitive 72, n.º 1 (2020): 123–39. http://dx.doi.org/10.3406/intel.2020.1949.
Texto completo da fonteCorredor, David, Anais Vallet, Maëlle Riou, Francis Eustache e Bérengère Guillery-Girard. "Les sciences des réseaux appliquées à l’étude du Trouble de Stress Post-Traumatique". Biologie Aujourd’hui 217, n.º 1-2 (2023): 79–87. http://dx.doi.org/10.1051/jbio/2023020.
Texto completo da fonteDABILGOU, Téré, Oumar SANOGO, S. Augustin Zongo, Tizane Daho, Belkacem Zeghmati, Jean KOULIDIATI e Antoine BERE. "Modélisation thermodynamique de combustion mono-zone de biodiesels dans un moteur diesel et estimation théorique des émissions potentielles". Journal de Physique de la SOAPHYS 2, n.º 1a (13 de fevereiro de 2021): C20A10–1—C20A10–10. http://dx.doi.org/10.46411/jpsoaphys.2020.01.10.
Texto completo da fonteYao, Marcel Konan, Lako Agbri, Siaka Barthélemy Bamba, Bernard Métongo Soro e Albert Trokourey. "Prédiction de l’évolution spatio-temporelle du fer à l’exutoire d’un fleuve tropical : cas du fleuve Sassandra à Gaoulou (Côte d’Ivoire)". International Journal of Biological and Chemical Sciences 10, n.º 6 (25 de abril de 2017): 2768. http://dx.doi.org/10.4314/ijbcs.v10i6.29.
Texto completo da fonteSAUVANT, Daniel, Laurence PUILLET e Bertrand BLUET. "Extension spatio-temporelle du modèle chèvre INRA 2018 : 2. L'évolution de la dynamique des réserves, du poids vif et de la NEC sur un cycle productif". INRAE Productions Animales 35, n.º 1 (17 de maio de 2022): 73–90. http://dx.doi.org/10.20870/productions-animales.2022.35.1.5492.
Texto completo da fonteTOKO ISSIAKA, Nourou, Soufouyane ZAKARI, Mama DJAOUGA, Yaya ISSIFOU MOUMOUNI e Brice A. TENTE. "Cartographie De La Dynamique Spatio-Temporelle Et De La Vulnerabilite Des Unites D'occupation Des Terres Dans Le Parc National Du W (Pnw) Au Benin". International Journal of Progressive Sciences and Technologies 46, n.º 1 (30 de agosto de 2024): 330. https://doi.org/10.52155/ijpsat.v46.1.6516.
Texto completo da fonteDab, William, Nathalie Beltzer e Jean-Paul Moatti. "Les modèles d'analyse des comportements à risque face à l'infection à VIH : une conception trop étroite de la rationalité". Population Vol. 48, n.º 5 (1 de maio de 1993): 1505–34. http://dx.doi.org/10.3917/popu.p1993.48n5.1534.
Texto completo da fonteEl-Jabi, N., G. Le-Kourdahi e D. Caissie. "Modélisation stochastique de la température de l'eau en rivière". Revue des sciences de l'eau 8, n.º 1 (12 de abril de 2005): 77–95. http://dx.doi.org/10.7202/705214ar.
Texto completo da fonteEscorcia, Dyanne, e Fabien Fenouillet. "Connaissances métacognitives et stratégies d’autorégulation impliquées dans la révision de textes : construction et validation d’un instrument autorapporté". Mesure et évaluation en éducation 41, n.º 2 (24 de abril de 2019): 1–36. http://dx.doi.org/10.7202/1059171ar.
Texto completo da fonteTeses / dissertações sobre o assunto "Prédiction temporelle"
Hadjoudja, Abdelkader. "Macrogénération et prédiction temporelle sur les réseaux programmables CPLD". Grenoble INPG, 1997. http://www.theses.fr/1997INPG0177.
Texto completo da fonteDeregnaucourt, Thomas. "Prédiction spatio-temporelle de surfaces issues de l'imagerie en utilisant des processus stochastiques". Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC088.
Texto completo da fonteThe prediction of a surface is now an important problem due to its use in multiple domains, such as computer vision, the simulation of avatars for cinematography or video games, etc. Since a surface can be static or dynamic, i.e. evolving with time, this problem can be separated in two classes: a spatial prediction problem and a spatio-temporal one. In order to propose a new approach for each of these problems, this thesis works have been separated in two parts.First of all, we have searched to predict a static surface, which is supposed cylindrical, knowing it partially from curves. The proposed approach consisted in deforming a cylinder on the known curves in order to reconstruct the surface of interest. First, a correspondence between known curves and the cylinder is generated with the help of shape analysis tools. Once this step done, an interpolation of the deformation field, which is supposed Gaussian, have been estimated using maximum likelihood and Bayesian inference. This methodology has then been applied to real data from two domains of imaging: medical imaging and infography. The obtained results show that the proposed approach exceeds the existing methods in the literature, with better results using Bayesian inference.In a second hand, we have been interested in the spatio-temporal prediction of dynamic surfaces. The objective was to predict a dynamic surface based on its initial surface. Since the prediction needs to learn on known observations, we first have developed a spatio-temporal surface analysis tool. This analysis is based on shape analysis tools, and allows a better learning. Once this preliminary step done, we have estimated the temporal deformation of the dynamic surface of interest. More precisely, an adaptation, with is usable on the space of surfaces, of usual statistical estimators has been used. Using this estimated deformation on the initial surface, an estimation of the dynamic surface has been created. This process has then been applied for predicting 4D expressions of faces, which allow us to generate visually convincing expressions
Langlois, Sébastien. "Prédiction des vibrations éoliennes d'un système conducteur-amortisseur avec une méthode temporelle non linéaire". Thèse, Université de Sherbrooke, 2013. http://hdl.handle.net/11143/6133.
Texto completo da fonteArrouet, Alana. "Exploration de la prédiction temporelle associée à la motricité chez les individus neurotypiques et neuro-atypiques". Electronic Thesis or Diss., Strasbourg, 2024. http://www.theses.fr/2024STRAJ067.
Texto completo da fonteThe aim of this thesis was to explore the impact of temporal prediction on movement planning and execution. We used motor tasks in which participants stopped an index finger movement in response to a predictable target signal and examined how this prediction influenced both movement preparation and stopping execution. In neurotypical individuals, our findings revealed multiple temporal prediction mechanisms operating simultaneously: one linked to motor commands affecting preparation, a sensorimotor prediction influencing execution, and an independent prediction reflecting cognitive anticipation. Sensorimotor temporal prediction evolves with development and appears to be impaired in individuals at high genetic risk of psychotic conversion. In people with schizophrenia, preliminary findings suggest that performing a movement may help restore temporal prediction abilities. This thesis provides insights into how temporal predictions are integrated into motor programs and raises questions about the mechanisms underlying sensorimotor integration
Lajugie, Rémi. "Prédiction structurée pour l’analyse de données séquentielles". Thesis, Paris, Ecole normale supérieure, 2015. http://www.theses.fr/2015ENSU0024/document.
Texto completo da fonteIn this manuscript, we consider structured machine learning problems and consider more precisely the ones involving sequential structure. In a first part, we consider the problem of similarity measure learning for two tasks where sequential structure is at stake: (i) the multivariate change-point detection and (ii) the time warping of pairs of time series. The methods generally used to solve these tasks rely on a similarity measure to compare timestamps. We propose to learn a similarity measure from fully labelled data, i.e., signals already segmented or pairs of signals for which the optimal time warping is known. Using standard structured prediction methods, we present algorithmically efficient ways for learning. We propose to use loss functions specifically designed for the tasks. We validate our approach on real-world data. In a second part, we focus on the problem of weak supervision, in which sequential data are not totally labeled. We focus on the problem of aligning an audio recording with its score. We consider the score as a symbolic representation giving: (i) a complete information about the order of events or notes played and (ii) an approximate idea about the expected shape of the alignment. We propose to learn a classifier for each note using this information. Our learning problem is based onthe optimization of a convex function that takes advantage of the weak supervision and of the sequential structure of data. Our approach is validated through experiments on the task of audio-to-score on real musical data
Jiga-Boy, Gabriela-Maria. "Adaptative thinking about the future : temporal construal, health-related behaviour and perceived temporal distance". Grenoble 2, 2008. http://www.theses.fr/2008GRE29032.
Texto completo da fonteThis thesis investigated a "functional paradox" between the importance we ascribe to being future-oriented in order to function efficiently and the quality of our future outlooks. The underlying processes signal that one is most of the time wrong when predicting future behaviours. We explored the way individuals construe future events and act on the basis of these representations (Chapter I). Drawing on construal level theory (Liberman & Trope, 1998), we first replicated the relationship between temporal distance and concrete/abstract construal of future events (Chapter II). Next, we failed to characterize construal of health-related behaviour using this pattern. These events were construed more concretely/abstractly irrespective of temporal distance of their enactment. We further investigated the factors shaping construal level and found that it varies with the personal relevance of information, the individual’s goals, and the goal-related actions he (she) is engaged in (Chapter III). Finally, in order to situate our actions in time, we explored how individuals perceive temporal distance to future events (Chapter IV). We found that effort to be invested in a future event shapes the perception of when the event happens: more effortful events are felt to be happening earlier than less effortful events. Overall, the findings reported in this thesis bring information about what underlies our future outlooks. They suggest that the way we represent our future actions is grounded in their personal context – in other words that our interests, motivations, and actions' personal relevancies shape the concreteness of our future actions’ construal
Hafid, Mohamed. "Prédiction par transfert inverse de l'évolution temporelle du front de solidification : applications aux réacteurs métallurgiques et à la cryochirurgie". Thèse, Université de Sherbrooke, 2017. http://hdl.handle.net/11143/10581.
Texto completo da fonteBossavy, Arthur. "Caractérisation et prédiction probabiliste des variations brusques et importantes de la production éolienne". Phd thesis, Ecole Nationale Supérieure des Mines de Paris, 2012. http://pastel.archives-ouvertes.fr/pastel-00803234.
Texto completo da fonteBehlouli, Hassan. "Apprentissages auto-améliorants et modélisation de la dynamique temporelle de données évolutives par réseaux de neurones : application au diagnostic et la prédiction en électrocardiologie quantitative". Lyon, INSA, 1998. http://www.theses.fr/1998ISAL0034.
Texto completo da fonteWe present various methodologies to improve decision making on follow-up patient data and their validation in the field of quantitative electrocardiology. First, we propose an extension to the classical Pattern Recognition supervised learning model by introducing a self-improving concept based on information min. Ing from undocumented datasets. Then we apply this concept to the particular case of neural networks based supervised learning and we propose a self-improving learning methodology integrating iteratively, in the initial learning set, undocumented data that are extracted from databases not validated by experts. This method involves different concepts such as neural network combination, rejection of ambiguous cases and control of the learning process by cross-validation. Using this approach for the categorisation of cardiac diseases we could significantly improve the performance of the original classifiers. Secondly, we developed a methodology based on neural networks to model the dynamic behavior of the heart particularly for predicting one of the main descriptors of the ventricular repolarisation, i. E. : the QT interval as a function of the RR interval that represents the inverse of heart rate. An initial evaluation on a series of sequences of 30 electrocardiograms (3D ECG) continuously '1 recorded over 24 hours allowed to demonstrate the pertinence of the models and to study the ray of some parameters (e. G. Memory effect and noise level) on the prediction quality of this model We conclude by presenting another outcome of our work, a series of generic analysis processing tool s that were integrated into the MATIS environment (Mathematical Tools Integration Software), which is a fundamental building black for the future workstation of the research cardiologist
Idir, Mohamed Yacine. "Analyse et développement de modèles statistiques pour l'estimation et la prédiction spatiale et temporelle de la pollution atmosphérique à partir de données issues de capteurs mobiles". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG107.
Texto completo da fonteUrban air pollution, a global health crisis causing millions of deaths every year, makes accurate mapping of this phenomenon not only relevant, but vital to public health.Currently, air quality is measured by fixed air quality monitoring stations. These reference stations provide a highly accurate measure of air quality, at the cost of limited spatial coverage.The idea of using new low-cost sensors developed from recent technological advances, smaller in size and incorporating a global positioning system (GPS), quickly emerged. This gives scientists additional tools to refine spatio-temporal maps of air pollution and create new datasets providing information on air quality that was previously unavailable.Generating precise air quality maps using these low-cost sensors presents several major challenges. These challenges are mainly related to the nature of the phenomenon being studied, and to the accuracy and volume of the data.Given these difficulties, it is important to know how to combine all these fuzzy data sources to obtain a clear picture of urban pollution.The aim of this thesis is to analyze and develop statistical models that exploit data acquired by low-cost mobile sensors. It contributes to the objective of providing more accurate spatial and temporal estimates and forecasts of urban air pollution, by combining mathematical models and technological advances
Capítulos de livros sobre o assunto "Prédiction temporelle"
ATTO, Abdourrahmane M., Aluísio PINHEIRO, Guillaume GINOLHAC e Pedro MORETTIN. "Analyse d’ordre fractionnaire et prédiction de trajectoire de cyclones". In Détection de changements et analyse des séries temporelles d’images 1, 159–82. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9056.ch6.
Texto completo da fonte