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Méthodes de classification des séries temporelles : application à un réseau de pluviomètres

Mohamed Djallel Dilmi 1, 2
LATMOS - Laboratoire Atmosphères, Milieux, Observations Spatiales
Abstract : The impact of climat change on the temporal evolution of precipitation as well as the impact of the Parisian heat island on the spatial distribution of précipitation motivate studying the varaibility of the water cycle on a small scale on île-de-france. one way to analyse this varaibility using the data from a rain gauge network is to perform a clustring on time series measured by this network. In this thesis, we have explored two approaches for time series clustring : for the first approach based on the description of series by characteristics, an algorithm for selecting characteristics based on genetic algorithms and topological maps has been proposed. for the second approach based on shape comparaison, a measure of dissimilarity (iterative downscaling time warping) was developed to compare two rainfall time series. Then the limits of the two approaches were discuddes followed by a proposition of a mixed approach that combine the advantages of each approach. The approach was first applied to the evaluation of spatial variability of precipitation on île-de-france. For the evaluation of the temporal variability of the precpitation, a clustring on the precipitation events observed by a station was carried out then extended on the whole rain gauge network. The application on the historical series of Paris-Montsouris (1873-2015) makes it possible to automatically discriminate "remarkable" years from a meteorological point of view.
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Submitted on : Monday, February 15, 2021 - 11:23:45 AM
Last modification on : Friday, December 3, 2021 - 11:42:54 AM
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  • HAL Id : tel-03141357, version 1


Mohamed Djallel Dilmi. Méthodes de classification des séries temporelles : application à un réseau de pluviomètres. Météorologie. Sorbonne Université, 2019. Français. ⟨NNT : 2019SORUS087⟩. ⟨tel-03141357⟩



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