MAADISON - Modèles par apprentissage automatisés pour la surveillance des ouvrages névralgiques | FEREC 2020

57 [13] Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani : An Introduction to Statistical Learning [14] Yiming Zhang, Hao Wang, Hua-Ping Wan, Jianxiao Mao : Anomaly detection of structural health monitoring data using the maximum likelihood estimation-based Bayesian dynamic linear model [15] Dominique Desbois : Introduction au test non paramétrique d’ajustement de Kolmogorov - Smirnov avec SPSS pour Windows. Cahiers des techniques de l’INRA, INRA, 2004, pp.41-62. hal-01072918 [16] Paparoditis, Efstathios, Politis, Dimitris N : The Asymptotic Size and Power of the Augmented Dickey-Fuller Test of a Unit Root, 2013-12-01 [17] Harry O. Posten : Robustness of the Two-Sample T-Test. Robustness of Statistical Methods and Nonparametric Statistics pp 92-99, 1984. [18] V.Monbet : Tests statistiques, notes de cours L2 S1-2009. [19] E- CUBE Strategy Consultants SA, Visium Technologies SA : Application de l’intelligence artificielle dans l’énergie https://tecsol. blogs.com/files/e-cube-ia-energie.pdf [20] Vincent Bouchet : Machine learning en finance : vers de nouvelles stratégies ? Gestion et management.2017. dumas-01706572 [21] Hyune-Ju Kim, Binbing Yu and Eric J.Feuer : Selecting the number of change-points in segmented line regression [22] Seif-Eddine Benkabou. Détecti on d’anomalies dans les séries temporelles : application aux masses de données sur les pneumatiques.Base de données [cs.DB ].Université de Lyon, 2018. [23] Rebecca Killick, Idris A.Eckley, Kevin Ewans, Phillip Jonathan : Detection of changes in variance of time- series using changepoint analysis [24] Gordon J.Ross Parametric and Nonparametric Sequential Change Detection in R : The cpm Package [25] Rebecca Killick and Idris A.Eckley : Changepoint : An R Package for Changepoint Analysis [26] Xiaofeng SHAO and Xianyang ZHANG Testing for Change Points in Time Series [27] Ahmed Tealab : Time series forecasting using artificial neural networks methodologies : A system review [28] Denis Kwiatkowski, Peter C.B. Phillips, Peter Schmidt and Yongcheol Shin Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?, Journal of Econometrics , Volume 54, Issues 1 – 3, October – December 1992, Pages 159-178 [29] Stéphane BONNEVAY : Réseaux de neurones et Deep Learning [30] https://qastack.fr/stats/30569/what-is-the-difference-between-a-stationary-test-and-a-unit-root-test [31] Stephane CHAMPELY : Tests stati stiques paramétriques : taille d’effett, puissance et taille d’échantillon [32] Efstathios Paparoditis & Dimitris N. Politis (2018) The asymptotic size and power of the augmented Dickey – Fuller test for a unit root, Econometric Reviews, 37:9, 955-973, DOI: 10.1080/00927872.2016.1178887. [33] Nicolas Manzini, Ndeye Mar, Franzi-ska Schmidt, Jean-François Bercher, André Orcesi, Pierre Marchand, Julien Gazeaux and Christian Thom : An automated machine learning-based approach for structural novelty detection based on SHM, Eurustruct 2021, 1st European Conference of the European Association on Quality Control of Bridges and Structures, 29th August to 1st September 2021, Padua.

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