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Academic literature on the topic 'Isolement des variables défectueuses'
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Journal articles on the topic "Isolement des variables défectueuses"
Salifu, D. A., T. B. Manga, and I. O. Onyali. "Enquête sur les parasites gastro-intestinaux chez des porcs du Nigeria (Plateau State et Rivers State)." Revue d’élevage et de médecine vétérinaire des pays tropicaux 43, no. 2 (February 1, 1990): 193–96. http://dx.doi.org/10.19182/remvt.8848.
Full textLanglois, Johanne, and Daniel Fortin. "Monoparentalité à chef féminin, pauvreté et santé mentale : état de la recherche." Santé mentale au Québec 19, no. 1 (September 11, 2007): 157–73. http://dx.doi.org/10.7202/032301ar.
Full textBegin, Simon. "Isolement et contentions: revue de littérature et focus sur leurs impacts et les normes qui les régissent." Canadian Journal of Psychiatry 36, no. 10 (December 1991): 752–59. http://dx.doi.org/10.1177/070674379103601014.
Full textBartoli, Henri. "La pensée économique au tournant du millénaire." Études internationales 29, no. 2 (April 12, 2005): 423–46. http://dx.doi.org/10.7202/703884ar.
Full textBenziane, Taoufiq, and Mireille Campan. "Effets d'un élevage en isolement sur le développement gonadotrope, la production d'hydrocarbures cuticulaires et le comportement sexuel de Calliphora vomitoria (Diptères, Calliphoridae)." Canadian Journal of Zoology 71, no. 6 (June 1, 1993): 1175–81. http://dx.doi.org/10.1139/z93-160.
Full textBouka Dipelet, Ulrich Gaël. "Structuration de la biodiversité des forêts africaines et changements climatiques : une étude à travers le genre Khaya (Meliaceae)." BOIS & FORETS DES TROPIQUES 339 (April 17, 2019): 95. http://dx.doi.org/10.19182/bft2019.339.a31718.
Full textVialou, Denis. "L’art des grottes en Ariège magdalénienne." Gallia préhistoire. Suppléments 22, no. 1 (1986): 5–28. http://dx.doi.org/10.3406/galip.1986.2542.
Full textDissertations / Theses on the topic "Isolement des variables défectueuses"
Yang, Junjie. "Fault Diagnosis and Prognosis in multivariate complex systems." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPAST001.
Full textFault diagnosis and prognosis have attracted huge attention in industry and academia for the increasing requirements on reliability, availability, maintainability, and safety.Despite the significant progress, the existing fault diagnosis methodologies still suffer from challenges, such as the lack of sufficient faulty data for training, ineffectiveness to complex distributed data, low sensitivity to incipient faults, and the interference of noise and outliers.Therefore, this work proposes a new one-class classification method implemented by generating anchors and selecting the region margin to determine a healthy region as a decision area.Then a particular distance measurement called local Mahalanobis distance is then defined to indicate the distance between a sample and the healthy region.Based on the proposed one-class classification method and the LMD index, this work first develops an incipient fault detection approach by combining the LMD index and the empirical probability density cumulative sum technique.This work also discusses the efficiency of LMD as a representative feature for fault detection.Secondly, this work proposes the faulty variable isolation method for single fault cases by combining the LMD technique with the contribution plot idea.Thirdly, an analytical expression of fault increasing rate is derived from the LMD index for the fault severity estimation task.Finally, we further develop a new reconstruction-based approach using the local Mahalanobis distance as a detection index to improve the isolation and estimation performance.The improved method can accurately isolate multiple faulty variables and estimate their fault amplitudes simultaneously.The case study based on the Continuous-flow Stirred Tank Reactor process data shows that the LMD technique has significant benefits for the fault diagnosis problem, such as high sensitivity to incipient faults, robustness to noise and outliers, and no distribution assumption.The fault diagnosis methods developed on LMD significantly outperform state-of-the-art solutions.The comparative study on the Case Western Reserve University bearing data indicates that the LMD technique can be used as a feature extraction approach and is more effective and robust than the other statistical techniques