Efficient recursive principal component analysis algorithms for process monitoring LM Elshenawy, S Yin, AS Naik, SX Ding Industrial & Engineering Chemistry Research 49 (1), 252-259, 2010 | 123 | 2010 |
Recursive fault detection and isolation approaches of time-varying processes LM Elshenawy, HA Awad Industrial & Engineering Chemistry Research 51 (29), 9812-9824, 2012 | 37 | 2012 |
Fault diagnosis of time-varying processes using modified reconstruction-based contributions LM Elshenawy, TA Mahmoud Journal of Process Control 70, 12-23, 2018 | 35 | 2018 |
Unsupervised Machine Learning Techniques for Fault Detection and Diagnosis in Nuclear Power Plants LM Elshenawy, MA Halawa, TA Mahmoud, HA Awad, MI Abdo Progress in Nuclear Energy 142, 103990, 2021 | 29 | 2021 |
Fault detection and diagnosis strategy based on k-nearest neighbors and fuzzy C-means clustering algorithm for industrial processes LM Elshenawy, C Chakour, TA Mahmoud Journal of the Franklin institute 359 (13), 7115-7139, 2022 | 22 | 2022 |
Simultaneous Fault Detection and Diagnosis Using Adaptive Principal Component Analysis and Multivariate Contribution Analysis LM Elshenawy, TA Mahmoud, C Chakour Industrial & Engineering Chemistry Research, 2020 | 21 | 2020 |
Direct Adaptive Control for Nonlinear Systems Using A TSK Fuzzy Echo State Network Based on Fractional-Order Learning Algorithm TA Mahmoud, MI Abdo, EA Elsheikh, LM Elshenawy Journal of the Franklin Institute, 2021 | 15 | 2021 |
Echo state neural network based state feedback control for SISO afine nonlinear systems TA Mahmoud, LM Elshenawy IFAC-PapersOnLine 48 (11), 354-359, 2015 | 15 | 2015 |
Model-based fault diagnosis via parameter estimation using knowledge base and fuzzy logic approach L Mohamed, AS Ibrahim 11th IEEE Mediterranean Electrotechnical Conference (IEEE Cat. No. 02CH37379 …, 2002 | 15 | 2002 |
Adaptive CIPCA-based fault diagnosis scheme for uncertain timevarying processes C Chakour, A Hamza, LM Elshenawy Neural Computing and Applications, 2021 | 10 | 2021 |
Observer-based echo-state neural network control for a class of nonlinear systems TA Mahmoud, LM Elshenawy Transactions of the Institute of Measurement and Control 40 (3), 930-939, 2018 | 8 | 2018 |
TSK fuzzy echo state neural network: a hybrid structure for black-box nonlinear systems identification TA Mahmoud, LM Elshenawy Neural Computing and Applications 34 (9), 7033-7051, 2022 | 7 | 2022 |
Fault detection of nonlinear processes using fuzzy c-means-based kernel PCA LM Elshenawy, TA Mohamed ICMLEME'2014, 318-324, 2014 | 4 | 2014 |
Direct adaptive control based on LS-SVM inverse model for nonlinear systems TA Mahmoud, LM Elshenawy 2014 19th International Conference on Methods and Models in Automation and …, 2014 | 2 | 2014 |
Fault detection of wind turbine system based on data-driven methods: a comparative study LM Elshenawy, AA Gafar, HA Awad, MS AbouOmar Neural Computing and Applications, 1-18, 2024 | | 2024 |
Data-Driven Soft Sensors Based on Support Vector Regression and Gray Wolf Optimizer MS AbouOmar, A Badawy, LM Elshenawy 2023 3rd International Conference on Electronic Engineering (ICEEM), 1-6, 2023 | | 2023 |
Attacks Detection in Industrial Cyber-Physical Systems Using Convolutional Neural Networks M Salah, LM Elshenawy 2023 3rd International Conference on Electronic Engineering (ICEEM), 1-6, 2023 | | 2023 |
Enhanced Efficiency and Scalability in WIM Systems using Smart Sensors and Centralized Processing MS Abosreea, LM Elshenawy, IH Hashim 2023 3rd International Conference on Electronic Engineering (ICEEM), 1-6, 2023 | | 2023 |
Fault detection and diagnosis strategy for wind turbine system using partial least square technique LM Elshenawy, AA Gafar, H Awad 2023 3rd International Conference on Electronic Engineering (ICEEM), 1-6, 2023 | | 2023 |
Fault Detection and Isolation Indices for Large-Scale Systems LM Elshenawy 2019 14th International Conference on Computer Engineering and Systems …, 2019 | | 2019 |