Dissertations / Theses on the topic 'Analyse des séries temporelles'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Analyse des séries temporelles.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
Le, Tertre Alain. "Séries temporelles et analyse combinée des liens pollution atmosphérique et santé." Paris 6, 2005. http://www.theses.fr/2005PA066434.
Full textDesrosiers, Maxime. "Le prix du risque idiosyncrasique : une analyse en séries temporelles et coupe transversale." Master's thesis, Université Laval, 2020. http://hdl.handle.net/20.500.11794/67076.
Full textToque, Carole. "Pour l'identification de modèles factoriels de séries temporelles : application aux ARMA stationnaires." Phd thesis, Télécom ParisTech, 2006. http://pastel.archives-ouvertes.fr/pastel-00001966.
Full textBen, othmane Zied. "Analyse et visualisation pour l'étude de la qualité des séries temporelles de données imparfaites." Thesis, Reims, 2020. http://www.theses.fr/2020REIMS002.
Full textThis thesis focuses on the quality of the information collected by sensors on the web. These data form time series that are incomplete, imprecise, and are on quantitative scales that are not very comparable. In this context, we are particularly interested in the variability and stability of these time series. We propose two approaches to quantify them. The first is based on a representation using quantiles, the second is a fuzzy approach. Using these indicators, we propose an interactive visualization tool dedicated to the analysis of the quality of the harvest carried out by the sensors. This work is part of a CIFRE collaboration with Kantar
Achouch, Ayman. "Analyse économétrique des prix des métaux : une application multivariée des méthodes statistiques aux séries temporelles." Montpellier 1, 1998. http://www.theses.fr/1998MON10025.
Full textHéas, Patrick. "Apprentissage bayésien de structures spatio-temporelles : application à la fouille visuelle de séries temporelles d'images de satellites." Toulouse, ENSAE, 2005. http://www.theses.fr/2005ESAE0004.
Full textKhaleghi, Azadeh. "Sur quelques problèmes non-supervisés impliquant des séries temporelles hautement dépendantes." Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2013. http://tel.archives-ouvertes.fr/tel-00920333.
Full textBouopda, Pierre Kamé. "Analyse des séries temporelles : une application à la modélisation macroéconomique des comportements bancaires dans le cas français." Paris 1, 1992. http://www.theses.fr/1992PA01A017.
Full textThis work deals with the recent methods of time series analysis in order to outline, in the French case, macroeconomic behaviors of banks. This view leads as to take account of stationary processes, integration and cointegration concepts within the whole of tests. Our empirical strategy is issued mainly, first, of Hendry's works upon data generating processes (DGP) and, at a second time on Engle and Granger's on error correction models (ECM). Our econometrical methodology aims to an homogene writing way of the specification, making our empirical models such as : liquidity in the banks, short terms credit interest rates, long term credit supplies and bonds supplies, essy to read, to analyse and underline good statistical performances
Collilieux, Xavier. "Analyse des séries temporelles de positions des stations de géodésie spatiale : application au Repère International de Référence Terrestre (ITRF)." Observatoire de Paris (1667-....), 2008. https://hal.science/tel-02095044.
Full textFor the first time of its history, the latest to date realization of the International Terrestrial Reference System, the ITRF2005, has been generated from station position time series of the four main space geodetic techniques: the Global Positioning System (GPS), the Very Long Baseline Interferometry (VLBI), the Satellite Laser Ranging (SLR), and the Doppler Orbit determination and Radiopositioning Integrated by Satellite (DORIS). The ITRF computation process consists in stacking the station positions of each technique individually and then combining those using local ties. Meanwhile, time series of station positions allow investigating not only their temporal variations but also global biases that affect reference frame determination. In addition, the current ITRF computation process is a good opportunity to study the agreement of the station position estimations from the space geodetic techniques. To be comparable to each other, global biases which affect stations positions from each technique need to be properly estimated and removed. We have developed some methods to limit the aliasing effect which occurs during this estimation process. These methods have been applied to compare station height time series from VLBI, SLR, and GPS and geocenter motion time series. These analyses have highlighted a certain agreement at the annual frequency, which expresses the detection of loading effects. The use of a loading model in secular frame estimation process is therefore recommended
Khodor, Nadine. "Analyse de la dynamique des séries temporelles multi-variées pour la prédiction d’une syncope lors d’un test d’inclinaison." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S123/document.
Full textSyncope is a sudden loss of consciousness. Although it is not usually fatal, it has an economic impact on the health care system and the personal lives of people suffering. The purpose of this study is to reduce the duration of the clinical test (approximately 1 hour) and to avoid patients to develop syncope by early predicting the occurrence of syncope. The entire work fits into a data mining approach involving the feature extraction, feature selection and classification. 3 complementary approaches are proposed, the first one exploits nonlinear analysis methods of time series extracted from signals acquired during the test, the second one focuses on time- frequency (TF) relation between signals and suggests new indexes and the third one, the most original, takes into account their temporal dynamics
Lê, Thu Trang. "Extraction d'informations de changement à partir des séries temporelles d'images radar à synthèse d'ouverture." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAA020/document.
Full textA large number of successfully launched and operated Synthetic Aperture Radar (SAR) satellites has regularly provided multitemporal SAR and polarimetric SAR (PolSAR) images with high and very high spatial resolution over immense areas of the Earth surface. SAR system is appropriate for monitoring tasks thanks to the advantage of operating in all-time and all-weather conditions. With multitemporal data, both spatial and temporal information can simultaneously be exploited to improve the results of researche works. Change detection of specific features within a certain time interval has to deal with a complex processing of SAR data and the so-called speckle which affects the backscattered signal as multiplicative noise.The aim of this thesis is to provide a methodology for simplifying the analysis of multitemporal SAR data. Such methodology can benefit from the advantages of repetitive SAR acquisitions and be able to process different kinds of SAR data (i.e. single, multipolarization SAR, etc.) for various applications. In this thesis, we first propose a general framework based on a spatio-temporal information matrix called emph{Change Detection Matrix} (CDM). This matrix contains temporal neighborhoods which are adaptive to changed and unchanged areas thanks to similarity cross tests. Then, the proposed method is used to perform three different tasks:1) multitemporal change detection with different kinds of changes, which allows the combination of multitemporal pair-wise change maps to improve the performance of change detection result;2) analysis of change dynamics in the observed area, which allows the investigation of temporal evolution of objects of interest;3) nonlocal temporal mean filtering of SAR/PolSAR image time series, which allows us to avoid smoothing change information in the time series during the filtering process.In order to illustrate the relevancy of the proposed method, the experimental works of the thesis is performed on four datasets over two test-sites: Chamonix Mont-Blanc, France and Merapi volcano, Indonesia, with different types of changes (i.e., seasonal evolution, glaciers, volcanic eruption, etc.). Observations of these test-sites are performed on four SAR images time series from single polarization to full polarization, from medium to high, very high spatial resolution: Sentinel-1, ALOS-PALSAR, RADARSAT-2 and TerraSAR-X time series
Bac, Catherine. "Saisonnalité et non stationnarité : une analyse en termes de séries temporelles avec applications à la boucle prix salaire et à la dynamique des stocks." Paris 1, 1994. http://www.theses.fr/1994PA010039.
Full textThis study concerns the analysis of seasonal problems with regard to statistical analysis of time series and to economic as well as econometric modelling. Many economic time series are characterised by large seasonal variations. In the first part, unit root tests are reported. These tests are performed over american wage price series. This application highlight some drawbacks of seasonal filtering. Then lee's test have been extended for the application of seasonal cointegration tothe monthly data case. The application to stocks and productioin variables for american industry enabled to point out long term equilibrium relationships for the textile industry. In a second part, we have study periodic models. Non stationarity test for a univariate serie with periodic structure has been studied. Estimation problems for a periodic structurein a multivariate model are also examined. The application to inventories series exhibits a seasonal behavior. The production smoothing hypothesis has been reexamined in a third part, taking into account seasonal variations. The moldel is estimated with a maximum likelihood criterion, using the dalman filter. However, the data donot validate this hypothesis. Finally, the various aspects examined in this study have contributed to outline the information carried by seasonal movements
Tatsa, Sylvestre. "Modélisation et prévision de la consommation horaire d'électricité au Québec : comparaison de méthodes de séries temporelles." Thesis, Université Laval, 2014. http://www.theses.ulaval.ca/2014/30329/30329.pdf.
Full textThis work explores the dynamics of residential electricity consumption in Quebec using hourly data from January 2006 to December 2010. We estimate three standard autoregressive models in time series analysis: the Holt-Winters exponential smoothing, the seasonal ARIMA model (SARIMA) and the seasonal ARIMA model with exogenous variables (SARIMAX). For the latter model, we focus on the effect of climate variables (temperature, relative humidity and dew point and cloud cover). Climatic factors have a significant impact on the short-term electricity consumption. The intra-sample and out-of-sample predictive performance of each model is evaluated with various adjustment indicators. Three out-of-sample time horizons are tested: 24 hours (one day), 72 hours (three days) and 168 hours (1 week). The SARIMA model provides the best out-of-sample predictive performance of 24 hours. The SARIMAX model reveals the most powerful out-of-sample time horizons of 72 and 168 hours. Additional research is needed to obtain predictive models fully satisfactory from a methodological point of view. Keywords: modeling, electricity, Holt-Winters, SARIMA, SARIMAX.
Cherif, Aymen. "Réseaux de neurones, SVM et approches locales pour la prévision de séries temporelles." Thesis, Tours, 2013. http://www.theses.fr/2013TOUR4003/document.
Full textTime series forecasting is a widely discussed issue for many years. Researchers from various disciplines have addressed it in several application areas : finance, medical, transportation, etc. In this thesis, we focused on machine learning methods : neural networks and SVM. We have also been interested in the meta-methods to push up the predictor performances, and more specifically the local models. In a divide and conquer strategy, the local models perform a clustering over the data sets before different predictors are affected into each obtained subset. We present in this thesis a new algorithm for recurrent neural networks to use them as local predictors. We also propose two novel clustering techniques suitable for local models. The first is based on Kohonen maps, and the second is based on binary trees
Sànchez, Pérez Andrés. "Agrégation de prédicteurs pour des séries temporelles, optimalité dans un contexte localement stationnaire." Thesis, Paris, ENST, 2015. http://www.theses.fr/2015ENST0051/document.
Full textThis thesis regroups our results on dependent time series prediction. The work is divided into three main chapters where we tackle different problems. The first one is the aggregation of predictors of Causal Bernoulli Shifts using a Bayesian approach. The second one is the aggregation of predictors of what we define as sub-linear processes. Locally stationary time varying autoregressive processes receive a particular attention; we investigate an adaptive prediction scheme for them. In the last main chapter we study the linear regression problem for a general class of locally stationary processes
Corbineau, Ana. "Variabilité temporelle des grands poissons pélagiques exploités dans les écosystèmes marins tropicaux." Paris 6, 2009. http://www.theses.fr/2009PA066257.
Full textZongo, Sylvie Brizard. "Fluctuations multi-échelles et extrêmes dans les séries temporelles biogéochimiques à moyen et long terme en milieu marin côtier." Thesis, Lille 1, 2010. http://www.theses.fr/2010LIL10135/document.
Full textThis thesis focuses on the study of biogeochemical time series in order to characterize the dynamics of their fluctuations on a wide range of scales, and in particular their extremes. The databases analyzed here are mainly provided by the MAREL and SOMLIT programmes. The MAREL program is a network of automatic measuring devices monitoring coastal marine environments implemented by Ifremer. The SOMLIT is a French national program operated by INSU. The measurements are made once every two weeks on the fixed stations. In order to analyze these time series, methods have been borrowed from the fields of numerical analysis and turbulence. The study was conducted in three parts. In the first part, we consider the high frequency time series. The Fourier spectral analysis reveals the influence of physical forcing on the distribution of the parameters. The second part of the study compares SOMLIT and MAREL results recorded from sites near Boulogne-sur-mer. The comparison of the two measuring systems (manual and automatic) showed that while they are complementary, the automatic MAREL system is more informative. The probability density functions (pdfs) of some ratios reveal extreme values in their dynamics. These pdfs reveal in all cases a hyperbolic behavior in the tail probability of the ratios. In the third part, we consider the influence of extremes events of the Seine flow on the distribution of some biogeochemical parameters. This section is also concerned with the analysis of data at high frequency in order to estimate of water masses state in the English Channel within the context of the Water Framework Directive (WFD)
Six, Delphine. "Analyse statistique des distributions spatiales et temporelles des séries de bilans de masse des glaciers alpins et des calottes polaires de l'hémisphère nord." Grenoble 1, 2000. http://www.theses.fr/2000GRE10255.
Full textTatard, Lucile. "Analyse statistique des glissements de terrain déclenchés : implications sur les contrôles sismiques et climatiques." Phd thesis, Grenoble, 2010. http://tel.archives-ouvertes.fr/tel-00498011.
Full textGong, Xing. "Analyse de séries temporelles d’images à moyenne résolution spatiale : reconstruction de profils de LAI, démélangeage : application pour le suivi de la végétation sur des images MODIS." Thesis, Rennes 2, 2015. http://www.theses.fr/2015REN20021/document.
Full textThis PhD dissertation is concerned with time series analysis for medium spatial resolution (MSR) remote sensing images. The main advantage of MSR data is their high temporal rate which allows to monitor land use. However, two main problems arise with such data. First, because of cloud coverage and bad acquisition conditions, the resulting time series are often corrupted and not directly exploitable. Secondly, pixels in medium spatial resolution images are often “mixed” in the sense that the spectral response is a combination of the response of “pure” elements.These two problems are addressed in this PhD. First, we propose a data assimilation technique able to recover consistent time series of Leaf Area Index from corrupted MODIS sequences. To this end, a plant growth model, namely GreenLab, is used as a dynamical constraint. Second, we propose a new and efficient unmixing technique for time series. It is in particular based on the use of “elastic” kernels able to properly compare time series shifted in time or of various lengths.Experimental results are shown both on synthetic and real data and demonstrate the efficiency of the proposed methodologies
Germain, Simon. "Conception d'une mesure automatisée de détection des changements alimentaires chez le porc." Mémoire, Université de Sherbrooke, 2015. http://hdl.handle.net/11143/7925.
Full textBen, Hamadou Radhouane. "Contribution à l'analyse spatio-temporelle de séries écologiques marines." Paris 6, 2003. http://www.theses.fr/2003PA066021.
Full textSicard, Pierre Louis. "Caractérisation des retombées atmosphériques en France en zone rurale sous forme de précipitations, gaz et aérosols. Analyse des tendances spatio-temporelles et des séries chronologiques." Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2007. http://tel.archives-ouvertes.fr/tel-00169222.
Full textEdjo, Ehouindo Marcellin Tiburce. "Analyse économétrique de la croissance, de la convergence et des changements structurels dans les pays de la zone FCFA : une approche par les séries temporelles." Dijon, 2003. http://www.theses.fr/2003DIJOE001.
Full textThis dissertation analyses the economic growth of FCFA area countries in the sight of events that are incorporated in Real GDP and real per capita GDP. By reminding the economic situation which prevailed in the period 1980-1993, we made the assumption that each country have experimented a structural change in order to show that taking into account this change leads to interesting economics implications in terms of growth and convergence analysis. The results show that in some countries, shocks have transitory effects and the real per capita GDP is generated by mechanisms of exogenous growth model. It also show that the series do not behave in homogeneous manner between countries, this tends to show that shocks on the economy are not homogeneous not only in terms of level, but also in terms of effects and break point. The convergence reveals a reduction of the real per capita GDP dispersion and seems to show the economic weight of C. E. M. A. C area in the convergence process. When we take into account the structural change in the stochastic convergence analysis the result reveals that the null hypothesis of no convergence is more often rejected than when the structural change is ignored in the analysis. In summary, all of the results in this dissertation confirm that the detected structural changes are not neutral in the growth and the convergence process of the economies
Sicard, Pierre. "Caractérisation des retombées atmosphériques en France en zone rurale sous forme de précipitations, gaz et aérosols : analyse des tendances spatio-temporelles et des séries chronologiques." Lille 1, 2006. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/2006/50376-2006-Sicard.pdf.
Full textGuégan, Dominique. "Modèles bilinéaires et polynomiaux de séries chronologiques : étude probabiliste et analyse statistique." Grenoble 1, 1988. http://tel.archives-ouvertes.fr/tel-00330671.
Full textBreton, Marc. "Application de méthodes de classification par séries temporelles au diagnostic médical et à la détection de changements statistiques et étude de la robustesse." Ecole Centrale de Lille, 2004. http://www.theses.fr/2004ECLI0005.
Full textWarembourg, Caroline. "Analyse temporelle du mésozooplancton dans la rade de Villefranche-sur-Mer à l'aide d'un nouveau système automatique d'imagerie numérique, le Zooscan : influence des apports particulaires, de la production primaire et des facteurs environnementaux." Paris 6, 2005. http://www.theses.fr/2005PA066469.
Full textHoang, Cong Tuan. "Prise en compte des fluctuations spatio-temporelles pluies-débits pour une meilleure gestion de la ressource en eau et une meilleure évaluation des risques." Phd thesis, Université Paris-Est, 2011. http://pastel.archives-ouvertes.fr/pastel-00658537.
Full textTran, Dinh Trong. "Analyse rapide et robuste des solutions GPS pour la tectonique." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00868030.
Full textAlari, Anna. "Variations temporelles et géographiques des méningites à pneumocoque et effet du vaccin conjugué en France." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLV070/document.
Full textStreptococcus pneumoniae is a Gram-positive commensal bacterium of the oropharyngeal flora usually colonizing human’s rhino pharynx, of which almost 100 serotypes are known. Infants and young children constitute its main reservoir. Pneumococcus may cause serious infections, such as meningitis, bacteremia and pneumonia, or less serious but more common such as sinusitis and acute otitis media (AOM). Two conjugate pneumococcal vaccines have been introduced in France: PCV7 (covering 7 serotypes) in 2003 and PCV13 (covering 6 additional serotypes) in 2010. The overall objective of this thesis is to assess the impact of vaccination policy on invasive pneumococcal diseases in France, by focusing on temporal and geographical trends of the most serious of them: pneumococcal meningitis (PM). An initial study of PMs temporal dynamics over the 2011-2014 period assessed the impact of conjugate vaccines’ introduction. Statistical modeling techniques were used for time series analysis. The results confirm the effects found in literature: a reduction of vaccine serotypes PMs but at the same time an increase of PMs, due to non-vaccine serotypes (effect of “serotype replacement”). Therefore, the first benefit of vaccine introduction at population scale has been observed no less than 11 years after PCV7 introduction, and then principally after PCV13 was introduced in 2010, with a 25% decrease in PMs in 2014. The geographic component was then implemented to analyze the role of vaccine coverage in annual PM variability between geographic units over the 2001-2016 period. Results confirm the effectiveness of both vaccine compositions on vaccine serotypes PMs and suggest homogeneity of this effect among geographic units. Conversely the serotype replacement has been confirmed only after the first vaccine composition was introduced and presents a variable and heterogeneous geographical repartition. Variability in vaccine coverage among geographic units doesn’t explain the differences in PMs, which could suggest the role of others factors such as demographic density. Finally, a dynamic modeling capable of taking into consideration fundamental aspects of pneumococcus transmission and infection mechanisms not integrated in static modeling has been proposed in order to predict the impacts of different vaccination strategies for 65+ adults and therefore assess their cost-utility ratios
Stephan, Gaëtan. "La déformation de la loi d'Okun au cours du cycle économique." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1G043/document.
Full textThis dissertation aims at study asymmetry of elasticity of unemployment to output in United States and Europe. In the first chapter, we employ a meta-analysis to identify the ``authentic'' value of Okun's law coefficient beyond publication bias. We show that measure of Okun's coefficient depends about the choice of endogenous variable. In the second chapter, it appears that Okun's law implies a labor productivity procyclical as firm practices labor hoarding. According our estimates, Okun's law presents significative evidence of asymmetry during recessions and recoveries especially since the mid-1980s when positive correlation between real GDP and productivity has disappeared. Conversely, in France and Germany, we observe a more stable Okun's coefficient along business cycle. The nature of macroeconomic movements in Europe could potentially explain these findings. Germany supports transitory and persistent movements in real GDP and unemployment. Nevertheless, macroeconomic movements in other European countries are driven by permanents shocks. In last chapter, we investigate asymmetric cointregration in a sample of European countries (France, Germany and United Kingdom), we show that asymmetric cointegration between real GDP and unemployment seems to be linked to an asymmetric Phillip's curve
Constant, Camille. "Modélisation stochastique et analyse statistique de la pulsatilité en neuroendocrinologie." Thesis, Poitiers, 2019. http://www.theses.fr/2019POIT2330.
Full textThe aim of this thesis is to propose several models representing neuronal calcic activity and unsderstand its applicatition in the secretion of GnRH hormone. This work relies on experience realised in INRA Centre Val de Loire. Chapter 1 proposes a continuous model, in which we examine a Markov process of shot-noise type. Chapter 2 studies a discrete model type AR(1), based on a discretization of the model from Chapter 1 and proposes a first estimation of the parameters. Chapter 3 proposes another dicrete model, type AR(1), in which the innovations are the sum of a Bernouilli variable and a Gaussian variable representing a noise, and taking into account a linear drift . Estimations of the parameters are given in order to detect spikes in neuronal paths. Chapter 4 studies a biological experience involving 33 neurons. With the modelisation of Chapter 3, we detect synchronization instants (simultaneous spkike of a high proportion of neurons of the experience) and then, using simulations, we test the quality of the method that we used and we compare it to an experimental approach
Besseau, Romain. "Analyse de cycle de vie de scénarios énergétiques intégrant la contrainte d’adéquation temporelle production-consommation." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLEM068.
Full textThis research work deals with the environmental impact assessment of energy. The current energy model, which supports the global economy, leads to major environmental impacts by contributing to climate change and resource depletion,and by degrading biodiversity and human health. The environmental impacts of energy systems are assessed, not only considering the energy generation phase, but the whole life-cycle of energy systems : from raw material extraction to end of life. As renewable energies are weather dependent, storage systems may become required to ensure the temporal balance between the production of energy and consumption when renewable energies reach high penetration rates. As a first step, parameterized life-cycle inventory models have been developed for the main energy technologies to produce orstore energy. Those models enable to account for the technological, spatial and temporal variability that can be important. As a second step, an approach based on times-series to model energy production as well as energy consumption has been developed. It allows assessing the energy storage needs induced by the weather dependency of the production and consumption.The global dynamic and parametric method to assess the life cycle environmental impact here developed has been appliedto self-consumption scenarios and then, to the insular territory of La Réunion. Those applications reveal that, even when accounting for the storage need induced by the weather dependency of the production, renewable energies present an environmental footprint significantly lower than the fossil counterparts they aim to substitute
Bédubourg, Gabriel. "Place des outils d'analyse des séries temporelles dans la surveillance épidémiologique pour la détection des épidémies et leur analyse : élaboration de nouveaux outils de détection et d'analyse étiologique des épidémies appliqués à la surveillance épidémiologique." Thesis, Aix-Marseille, 2018. http://www.theses.fr/2018AIXM0739.
Full textPublic health surveillance is the ongoing, systematic collection, analysis, interpretation, and dissemination of data for use in public health action to reduce morbidity and mortality of health-related events and to improve health. One of its objectives is the detection of unusualevents, i.e. outbreaks, requiring the rapid implementation of countermeasures.The objectives of this work are: (i) to evaluate the main published statistical methods for outbreak detection commonly implemented in different public health surveillance systems, (ii) to propose a new approach based on the optimal combination of statistical methods foroutbreak detection and benchmark it to other methods; and (iii) develop a new statistical method for the etiological analysis of an outbreak from public health surveillance data routinely collected by the system. To achieve these objectives, as a first step, we evaluate the main statistical methods, from a published set of simulated public health surveillance data. Statistical methods have been evaluated for an operational purpose: for all simulated time series, we used the tuning parameters recommended by their authors for each algorithm when available. We propose sensitivity and specificity metrics suitable for these tools. Then we propose an original approach for outbreak detection based on combination of methods selected in the previous step. The performance of this approach is compared to the previous ones according to the methodology implemented in the first step.Finally, we propose a method for the etiological analysis of an outbreak from surveillance data by using statistical models suitable for time series analysis
Phan, Thi-Thu-Hong. "Elastic matching for classification and modelisation of incomplete time series." Thesis, Littoral, 2018. http://www.theses.fr/2018DUNK0483/document.
Full textMissing data are a prevalent problem in many domains of pattern recognition and signal processing. Most of the existing techniques in the literature suffer from one major drawback, which is their inability to process incomplete datasets. Missing data produce a loss of information and thus yield inaccurate data interpretation, biased results or unreliable analysis, especially for large missing sub-sequence(s). So, this thesis focuses on dealing with large consecutive missing values in univariate and low/un-correlated multivariate time series. We begin by investigating an imputation method to overcome these issues in univariate time series. This approach is based on the combination of shape-feature extraction algorithm and Dynamic Time Warping method. A new R-package, namely DTWBI, is then developed. In the following work, the DTWBI approach is extended to complete large successive missing data in low/un-correlated multivariate time series (called DTWUMI) and a DTWUMI R-package is also established. The key of these two proposed methods is that using the elastic matching to retrieving similar values in the series before and/or after the missing values. This optimizes as much as possible the dynamics and shape of knowledge data, and while applying the shape-feature extraction algorithm allows to reduce the computing time. Successively, we introduce a new method for filling large successive missing values in low/un-correlated multivariate time series, namely FSMUMI, which enables to manage a high level of uncertainty. In this way, we propose to use a novel fuzzy grades of basic similarity measures and fuzzy logic rules. Finally, we employ the DTWBI to (i) complete the MAREL Carnot dataset and then we perform a detection of rare/extreme events in this database (ii) forecast various meteorological univariate time series collected in Vietnam
Lohier, Théophile. "Analyse temporelle de la dynamique de communautés végétales à l'aide de modèles individus-centrés." Thesis, Clermont-Ferrand 2, 2016. http://www.theses.fr/2016CLF22683/document.
Full textPlant communities are complex systems in which multiple species differing by their functional attributes interact with their environment and with each other. Because of the number and the diversity of these interactions the mechanisms that drive the dynamics of theses communities are still poorly understood. Modelling approaches enable to link in a mechanistic fashion the process driving individual plant or population dynamics to the resulting community dynamics. This PhD thesis aims at developing such approaches and to use them to investigate the mechanisms underlying community dynamics. We therefore developed two modelling approaches. The first one is based on a stochastic modelling framework allowing to link the population dynamics to the community dynamics whilst taking account of intra- and interspecific interactions as well as environmental and demographic variations. This approach is easily applicable to real systems and enables to describe the properties of plant population through a small number of demographic parameters. However our work suggests that there is no simple relationship between these parameters and plant functional traits, while they are known to drive their response to extrinsic factors. The second approach has been developed to overcome this limitation and rely on the individual-based model Nemossos that explicitly describes the link between plant functioning and community dynamics. In order to ensure that Nemossos has a large application potential, a strong emphasis has been placed on the tradeoff between realism and parametrization cost. Nemossos has then been successfully parameterized from trait values found in the literature, its realism has been demonstrated and it has been used to investigate the importance of temporal environmental variability for the coexistence of functionally differing species. The complementarity of the two approaches allows us to explore various fundamental questions of community ecology including the impact of competitive interactions on community dynamics, the effect of environmental filtering on their functional composition, or the mechanisms favoring the coexistence of plant species. In this work, the two approaches have been used separately but their coupling might offer interesting perspectives such as the investigation of the relationships between plant functioning and population dynamics. Moreover each of the approaches might be used to run various simulation experiments likely to improve our understanding of mechanisms underlying community dynamics
Padonou, Esperan. "Apprentissage Statistique en Domaine Circulaire Pour la Planification de Contrôles en Microélectronique." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEM009/document.
Full textDriven by industrial needs in microelectronics, this thesis is focused on probabilistic models for spatial data and Statistical Process Control. The spatial problem has the specificity of being defined on circular domains. It is addressed through a Kriging model where the deterministic part is made of orthogonal polynomials and the stochastic term represented by a Gaussian process. Defined with the Euclidean distance and the uniform measure over the disk, traditional Kriging models do not exploit knowledge on manufacturing processes. To take rotations or diffusions from the center into account, we introduce polar Gaussian processes over the disk. They embed radial and angular correlations in Kriging predictions, leading to significant improvements in the considered situations. Polar Gaussian processes are then interpreted via Sobol decomposition and generalized in higher dimensions. Different designs of experiments are developed for the proposed models. Among them, Latin cylinders reproduce in the space of polar coordinates the properties of Latin hypercubes. To model spatial and temporal data, Statistical Process Control is addressed by monitoring Kriging parameters, based on standard control charts. Furthermore, the monitored time – series contain outliers and structural changes, which cause bias in prediction and false alarms in risk management. These issues are simultaneously tackled with a robust and adaptive smoothing
Chen, Yu. "Analyse InSAR des déformations de volcans actifs : le Piton de la Fournaise (Réunion) et Llaima (Chili)." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30019.
Full textWe address in this dissertation the use of Interferometric Synthetic Aperture Radar (InSAR) to measure and characterize the ground surface deformation at two volcanoes - Piton de la Fournaise (La Réunion Island, France) and Llaima (Chile). For Piton de la Fournaise, we analyzed the spatial pattern and temporal evolution of the ground displacement between the historical March-April 2007 eruption and October 2014, based on continuous measurements recorded by GNSS stations and X band COSMO-SkyMed and TerraSAR-X/TanDEM-X time series analysis. For the processing of radar data, we adopted a classical InSAR time series approach that exploits the information redundancy in the interferograms and we implemented an original method for correcting artifacts based on the principal component decomposition. The spatial and temporal complexity of the obtained deformation field indicates that an important part of the volcanic edifice is affected by deformations of various origins that overlap spatially and temporally. We observe also subsidence processes that are not accompanied by horizontal displacements in recent lava fields. We show that there exists a linear relationship between the subsidence and the thickness of lava and that the amplitude of subsidence decreases with time. These relationships allow us to construct an empirical law to estimate the contribution of post-lava emplacement process in the deformation field. We also observe that the Central Cone subsides persistently during the study period. We interpret this subsidence as the expression of a relaxation of the stresses caused by the Dolomieu collapse during the March-April 2007 eruption. Finally, we show that a widespread time-dependent moving sector on the Eastern Flank is affected by downslope motion during the 2007-2014 period. The uncertainties on both the structure and rheology parameters of the edifice leads us to explore different hypotheses to explain the origin of this flank motion which could be controlled by the frictional properties of the rocks along one or more fault planes, or be the expression of a dependent ductile deformation of the viscosity of the medium. Llaima is a large Andean stratospheric volcano whose deformation processes are poorly understood not only because of the complexity of its functioning mode but also because of the absence of observation networks on the ground. In this context, the potential of radar data for monitoring the ground deformations of these volcanoes is a main scientific interest. However, the complex environment conditions (steep slopes, snow- or ice-capped summit, dense vegetation cover, and strong tropospheric artifacts) and limited amount of available radar data make it challenging to accurately measure ground displacement with InSAR
Mure, Simon. "Classification non supervisée de données spatio-temporelles multidimensionnelles : Applications à l’imagerie." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI130/document.
Full textDue to the dramatic increase of longitudinal acquisitions in the past decades such as video sequences, global positioning system (GPS) tracking or medical follow-up, many applications for time-series data mining have been developed. Thus, unsupervised time-series data mining has become highly relevant with the aim to automatically detect and identify similar temporal patterns between time-series. In this work, we propose a new spatio-temporal filtering scheme based on the mean-shift procedure, a state of the art approach in the field of image processing, which clusters multivariate spatio-temporal data. We also propose a hierarchical time-series clustering algorithm based on the dynamic time warping measure that identifies similar but asynchronous temporal patterns. Our choices have been motivated by the need to analyse magnetic resonance images acquired on people affected by multiple sclerosis. The genetics and environmental factors triggering and governing the disease evolution, as well as the occurrence and evolution of individual lesions, are still mostly unknown and under intense investigation. Therefore, there is a strong need to develop new methods allowing automatic extraction and quantification of lesion characteristics. This has motivated our work on time-series clustering methods, which are not widely used in image processing yet and allow to process image sequences without prior knowledge on the final results
Pouget, Fabien. ""Système distribué de capteurs pots de miel: discrimination et analyse corrélative des processus d'attaques"." Phd thesis, Télécom ParisTech, 2006. http://pastel.archives-ouvertes.fr/pastel-00001751.
Full textJoliveau, Marc. "Réduction de séries chronologiques de trafic routier urbain issues d'un réseau de capteurs géoréférencés et extraction de motifs spatio-temporels." Châtenay-Malabry, Ecole centrale de Paris, 2008. http://www.theses.fr/2008ECAP1087.
Full textTudesque, Loïc. "Analyse temporelle et spatiale des composantes chimiques, hydromorphologiques et diatomiques en relation avec les changements globaux." Toulouse 3, 2011. http://thesesups.ups-tlse.fr/1474/.
Full textThis thesis aimed at assessing the effect of global changes on aquatic ecosystems. The exploratory analysis of the land cover patterns, physicochemical, hydromorphological, and diatom databases in the Adour-Garonne basin and the diatom flora of streams in French Guyana highlighted: 1) the effect of the global changes on the water quality characterized by the temperature increase and the significant mitigation of eutrophication ; 2) the strongest influence of the land cover patterns at the catchment scale ; 3) the persistence of the diatom flora and the change of community structures facing extreme stress due to gold mining ; These results testified their importance as for their potential transfers towards the fields of "applied research", particularly proposing: 1) a temporal reference frame of the chemical water quality of the Adour-Garonne basin ; 2) to integrate the land cover patterns extracted at the catchment scale in order to improve or develop new biomonitoring tools ; 3) the development of a new generic diatom index appropriate to the French Guyana context based on the diatom motility abilities
Martini, Severine. "La bioluminescence : un proxy d'activité biologique en milieu profond ? Etude au laboratoire et in situ de la bioluminescence en relation avec les variables environnementales." Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4085/document.
Full textBioluminescence is the emission of light by living organisms. In the bathypelagic waters, where darkness is one of the main characteristic, this phenomenon seems to play a major role for biological interactions and in the carbon cycle. This work aims to determine if bioluminescence can be considered as a proxy of biological activity in the deep sea. This multidisciplinary study develops both in situ and laboratory approaches. The ANTARES telescope immersed in the Mediterranean Sea at 2,475 m depth has been used as an oceanographic observatory recording bioluminescence as well as environmen- tal variables at high frequency. This time series analysis, defined as non linear and non stationary, highlighted two periods of high bioluminescence intensity in 2009 and 2010. These events have been explained by convection phenomena in the Gulf of Lion, indi- rectly impacting the bioluminescence sampled at this station. In the laboratory, bacterial bioluminescence has been described using a piezophilic bacterial model isolated during a high-bioluminescence-intensity event. Hydrostatic pressure linked to the in situ depth (22 MPa) induces a higher bioluminescence activity than under atmospheric pressure (0.1 MPa). Then, the survey of the deep prokaryotic communities has been done at the AN- TARES station, over the year 2011. This survey shows the presence of about 0.1 to 1% of bioluminescent bacteria even during a low-bioluminescence-activity period. These cells were mainly actives
Marti, Gautier. "Some contributions to the clustering of financial time series and applications to credit default swaps." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX097/document.
Full textIn this thesis we first review the scattered literature about clustering financial time series. We then try to give as much colors as possible on the credit default swap market, a relatively unknown market from the general public but for its role in the contagion of bank failures during the global financial crisis of 2007-2008, while introducing the datasets that have been used in the empirical studies. Unlike the existing body of literature which mostly offers descriptive studies, we aim at building models and large information systems based on clusters which are seen as basic building blocks: These foundations must be stable. That is why the work undertaken and described in the following intends to ground further the clustering methodologies. For that purpose, we discuss their consistency and propose alternative measures of similarity that can be plugged in the clustering methodologies. We study empirically their impact on the clusters. Results of the empirical studies can be explored at www.datagrapple.com
Agoua, Xwégnon. "Développement de méthodes spatio-temporelles pour la prévision à court terme de la production photovoltaïque." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEM066/document.
Full textThe evolution of the global energy context and the challenges of climate change have led to anincrease in the production capacity of renewable energy. Renewable energies are characterized byhigh variability due to their dependence on meteorological conditions. Controlling this variabilityis an important challenge for the operators of the electricity systems, but also for achieving the Europeanobjectives of reducing greenhouse gas emissions, improving energy efficiency and increasing the share of renewable energies in EU energy consumption. In the case of photovoltaics (PV), the control of the variability of the production requires to predict with minimum errors the future production of the power stations. These forecasts contribute to increasing the level of PV penetration and optimal integration in the power grid, improving PV plant management and participating in electricity markets. The objective of this thesis is to contribute to the improvement of the short-term predictability (less than 6 hours) of PV production. First, we analyze the spatio-temporal variability of PV production and propose a method to reduce the nonstationarity of the production series. We then propose a deterministic prediction model that exploits the spatio-temporal correlations between the power plants of a spatial grid. The power stationsare used as a network of sensors to anticipate sources of variability. We also propose an automaticmethod for selecting variables to solve the dimensionality and sparsity problems of the space-time model. A probabilistic spatio-temporal model has also been developed to produce efficient forecasts not only of the average level of future production but of its entire distribution. Finally, we propose a model that exploits observations of satellite images to improve short-term forecasting of PV production
Guigou, Fabio. "The artificial immune ecosystem : a scalable immune-inspired active classifier, an application to streaming time series analysis for network monitoring." Thesis, Strasbourg, 2019. http://www.theses.fr/2019STRAD007/document.
Full textSince the early 1990s, immune-inspired algorithms have tried to adapt the properties of the biological immune system to various computer science problems, not only in computer security but also in optimization and classification. This work explores a different direction for artificial immune systems, focussing on the interaction between subsystems rather than the biological processes involved in each one. These patterns of interaction in turn create the properties expected from immune systems, namely their ability to detect anomalies, memorize their signature to react quickly upon secondary exposure, and remain tolerant to symbiotic foreign organisms such as the intestinal fauna. We refer to a set of interacting systems as an ecosystem, thus this new approach has called the Artificial Immune Ecosystem. We demonstrate this model in the context of a real-world problem where scalability and performance are essential: network monitoring. This entails time series analysis in real time with an expert in the loop, i.e. active learning instead of supervised learning
Benhmida, Saïd. "Robustesse et comportement asymptotique d'un TRA-estimateur des coefficients d'un processus ARMA (p,q)." Nancy 1, 1995. http://www.theses.fr/1995NAN10035.
Full textFaure, Cynthia. "Détection de ruptures et identification des causes ou des symptômes dans le fonctionnement des turboréacteurs durant les vols et les essais." Thesis, Paris 1, 2018. http://www.theses.fr/2018PA01E059/document.
Full textAnalysing multivariate time series created by sensors during a flight or a bench test represents a new challenge for aircraft engineers. Each time series can be decomposed univariately into a series of stabilised phases, well known by the expert, and transient phases that are merely explored but very informative when the engine is running. Our project aims at converting these time series into a succession of labels, designing transient and stabilised phases in a bivariate context. This transformation of the data will allow several perspectives: tracking similar behaviours or bivariate patterns seen during a flight, finding similar curves from a given curve, identifying the atypical curves, detecting frequent or rare sequences of labels during a flight, discovering hidden multivariate structures, modelling a representative flight, and spotting unusual flights. This manuscript proposes : methodology to automatically identify transient and stabilized phases, cluster all engine transient phases, label multivariate time series and analyse them. All algorithms are applied on real flight measurements with a validation of the results from expert knowledge
Beaufils, Bertrand. "Topological Data Analysis and Statistical Learning for measuring pedestrian activities from inertial sensors." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASS107.
Full textThis thesis focuses on the detection of specific movements using ActiMyo, a device developed by the company Sysnav. This system is composed by low-cost miniature inertial sensors that can be worn on the ankle and wrist. In particular, a supervised statistical learning approach aims to detect strides in ankle recordings. This first work, combined with an algorithm patented by Sysnav, allows to compute the trajectory of the pedestrian. This trajectory is then used in a new supervised learning method for the activity recognition, which is valuable information, especially in a medical context. These two algorithms offer an innovative approach based on the alignment of inertial signals and the extraction of candidate intervals which are then classified by the Gradient Boosting Trees algorithm. This thesis also presents a neural network architecture combining convolutional channels and topological data analysis for the detection of movements representative of Parkinson’s disease such as tremors and dyskinesia crises