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Fault detection of uncertain nonlinear process using interval-valued data-driven approach.

, , , , , и . SSD, стр. 585-590. IEEE, (2020)

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Abdelmalek Nasraoui

Abdelmalek Nigro

 

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Machine Learning based Multiscale Reduced Kernel PCA for Nonlinear Process Monitoring., , , , , и . SSD, стр. 302-307. IEEE, (2020)Multivariate feature extraction based supervised machine learning for fault detection and diagnosis in photovoltaic systems., , , , , , и . Eur. J. Control, (2021)Machine Learning based Reduced Kernel PCA for Nonlinear Process Monitoring., , , , и . IINTEC, стр. 180-185. IEEE, (2019)Fault detection in photovoltaic systems using machine learning technique., , , , , , и . SSD, стр. 207-212. IEEE, (2020)Uncertainty Quantification Kernel PCA: Enhancing Fault Detection in Interval-Valued Data., , , , , и . CoDIT, стр. 3021-3026. IEEE, (2024)Online monitoring scheme using principal component analysis through Kullback-Leibler divergence analysis technique for fault detection., , , и . Trans. Inst. Meas. Control, 42 (6): 1225-1238 (2020)Enhancing Fault Detection in Stochastic Environments Using Interval-Valued KPCA: A Cement Rotary Kiln Case Study., , , , и . IEEE Access, (2025)Fault detection of uncertain nonlinear process using interval-valued data-driven approach., , , , , и . SSD, стр. 585-590. IEEE, (2020)Machine learning approaches for fault detection and diagnosis of induction motors., , , , , , и . SSD, стр. 692-698. IEEE, (2020)Faults Classification in Grid-Connected Photovoltaic Systems., , , , , и . SSD, стр. 1431-1437. IEEE, (2021)