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Ahmed Ragab
Ahmed Ragab
Adjunct Professor, Polytechnique Montreal
Dirección de correo verificada de ivado.ca
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Fault diagnosis in industrial chemical processes using interpretable patterns based on Logical Analysis of Data
A Ragab, M El-Koujok, B Poulin, M Amazouz, S Yacout
Expert Systems with Applications 95, 368-383, 2018
782018
Remaining useful life prediction using prognostic methodology based on logical analysis of data and Kaplan–Meier estimation
A Ragab, MS Ouali, S Yacout, H Osman
Journal of Intelligent Manufacturing 27, 943-958, 2016
682016
Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling, and machine learning techniques: A comprehensive review and outlook
OM Abdeldayem, AM Dabbish, MM Habashy, MK Mostafa, M Elhefnawy, ...
Science of The Total Environment 803, 149834, 2022
652022
Prognostics of multiple failure modes in rotating machinery using a pattern-based classifier and cumulative incidence functions
A Ragab, S Yacout, MS Ouali, H Osman
Journal of Intelligent Manufacturing 30, 255-274, 2019
652019
Recent advances in the theory and practice of logical analysis of data
M Lejeune, V Lozin, I Lozina, A Ragab, S Yacout
European Journal of Operational Research 275 (1), 1-15, 2019
442019
Deep understanding in industrial processes by complementing human expertise with interpretable patterns of machine learning
A Ragab, M El Koujok, H Ghezzaz, M Amazouz, MS Ouali, S Yacout
Expert Systems with Applications 122, 388-405, 2019
312019
A multiagent-based methodology for known and novel faults diagnosis in industrial processes
M El Koujok, A Ragab, H Ghezzaz, M Amazouz
IEEE Transactions on Industrial Informatics 17 (5), 3358-3366, 2020
292020
Large-scale empirical study of important features indicative of discovered vulnerabilities to assess application security
M Zhang, XDC De Carnavalet, L Wang, A Ragab
IEEE Transactions on Information Forensics and Security 14 (9), 2315-2330, 2019
282019
Adaptive prognostics in a controlled energy conversion process based on long-and short-term predictors
M Soualhi, M El Koujok, KTP Nguyen, K Medjaher, A Ragab, H Ghezzaz, ...
Applied Energy 283, 116049, 2021
212021
Pattern‐based prognostic methodology for condition‐based maintenance using selected and weighted survival curves
A Ragab, S Yacout, MS Ouali, H Osman
Quality and Reliability Engineering International 33 (8), 1753-1772, 2017
202017
Fault detection and diagnosis in the Tennessee Eastman Process using interpretable knowledge discovery
A Ragab, M El-Koujok, M Amazouz, S Yacout
2017 annual reliability and maintainability symposium (RAMS), 1-7, 2017
192017
Fault classification in the process industry using polygon generation and deep learning
M Elhefnawy, A Ragab, MS Ouali
Journal of Intelligent Manufacturing 33 (5), 1531-1544, 2022
182022
Data-driven dynamic causality analysis of industrial systems using interpretable machine learning and process mining
K Nadim, A Ragab, MS Ouali
Journal of Intelligent Manufacturing, 2022
132022
High-temperature modeling of the IV characteristics of GaN150 HEMT using machine learning techniques
A Abubakr, A Hassan, A Ragab, S Yacout, Y Savaria, M Sawan
2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2018
102018
A data-driven causality analysis tool for fault diagnosis in industrial processes
E Alizadeh, M El Koujok, A Ragab, M Amazouz
IFAC-PapersOnLine 51 (24), 147-152, 2018
102018
Remaining useful life prognostics using pattern-based machine learning
A Ragab, S Yacout, MS Ouali
2016 Annual Reliability and Maintainability Symposium (RAMS), 1-7, 2016
102016
Multiple failure modes prognostics using logical analysis of data
A Ragab, S Yacout, MS Ouali, H Osman
2015 Annual Reliability and Maintainability Symposium (RAMS), 1-7, 2015
92015
Interpretable pattern-based machine learning for condition-based maintenance
A Ragab, S Yacout, MS Ouali
82015
Decision fusion for reliable fault classification in energy-intensive process industries
A Ragab, H Ghezzaz, M Amazouz
Computers in Industry 138, 103640, 2022
72022
A multi-agent approach based on machine-learning for fault diagnosis
M El Koujok, A Ragab, M Amazouz
IFAC-PapersOnLine 52 (10), 103-108, 2019
72019
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