overview

Dr. Nounou's research interests are in the area of process systems engineering with a particular emphasis on process modeling, estimation, fault detection, and control. The algorithms and tools developed in Dr. Nounou's research are utilized in many applications to improve the operation of various chemical, environmental, biological, and electrical systems.

education and training
selected publications
Academic Articles110
  • Dhibi, K., Fezai, R., Mansouri, M., Trabelsi, M., Bouzrara, K., Nounou, H. N., & Nounou, M. N. (2021). A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation.. 9, 64267-64277.
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  • Dhibi, K., Mansouri, M., Bouzrara, K., Nounou, H., & Nounou, M. (2021). An Enhanced Ensemble Learning-Based Fault Detection and Diagnosis for Grid-Connected PV Systems. IEEE Access. 9, 155622-155633.
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  • Mansouri, M., Trabelsi, M., Nounou, H., & Nounou, M. (2021). Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects. IEEE Access. 9, 126286-126306.
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  • Mansouri, M., Destain, M., Nounou, H., & Nounou, M. (2021). Enhanced Monitoring of Environmental Processes. International Journal of Environmental Science and Development. 7(7), 525-531.
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  • Baklouti, I., Mansouri, M., Hamida, A. B., Nounou, H. N., & Nounou, M. N. (2021). Enhanced operation of wastewater treatment plant using state estimation-based fault detection strategies.. 94, 300-311.
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Chapters9
  • Mansouri, M., Harkat, M., Nounou, H. N., & Nounou, M. N. (2020). Chapter 7 Conclusions and perspectives. Data-Driven and Model-Based Methods for Fault Detection and Diagnosis. 259-278. Elsevier.
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  • Ziyan Sheriff, M., Basha, N., Nazmul Karim, M., Nounou, H., & Nounou, M. (2020). Fault Detection of Single and Interval Valued Data Using Statistical Process Monitoring Techniques. Fault Detection, Diagnosis and Prognosis. IntechOpen.
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  • Sheriff, M. Z., Botre, C., Mansouri, M., Nounou, H., Nounou, M., & Karim, M. N. (2017). Process Monitoring Using Data-Based Fault Detection Techniques: Comparative Studies. Fault Diagnosis and Detection. InTech.
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  • Chaabane, M., Baklouti, I., Mansouri, M., Jaoua, N., Nounou, H., Nounou, M., Hamida, A. B., & Destain, M. (2016). Nonlinear State and Parameter Estimation Using Iterated Sigma Point Kalman Filter: Comparative Studies. Nonlinear Systems - Design, Analysis, Estimation and Control. InTech.
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  • Mansouri, M., Nounou, H., & Nounou, M. (2016). State Estimation and Process Monitoring of Nonlinear Biological Phenomena Modeled by S-systems. Computational Biology and Bioinformatics. 305-330. CRC Press.
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Conference Papers95
  • Belguesmi, L., Hajji, M., Mansouri, M., Harkat, M., Kouadri, A., Nounou, H., & Nounou, M. (2020). Machine learning approaches for fault detection and diagnosis of induction motors. 00, 692-698.
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  • Fezai, R., Abodayeh, K., Mansouri, M., Nounou, H., & Nounou, M. (2019). Diagnosis of nonlinear systems using reduced kernel principal component analysis. 00, 1-6.
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  • Fazai, R., Mansouri, M., Abodayeh, K., Trabelsi, M., Nounou, H., & Nounou, M. (2019). Machine Learning-Based Statistical Hypothesis Testing for Fault Detection. 00, 38-43.
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  • Fezai, R., Mansouri, M., Bouguila, N., Nounou, H., & Nounou, M. (2019). Machine learning based Gaussian process regression for fault detection of Biological Systems. 00, 174-179.
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  • Fazai, R., Mansouri, M., Abodayeh, K., Puig, V., Selmi, M., Nounou, H., & Nounou, M. (2019). Multiscale Gaussian Process Regression-Based GLRT for Water Quality Monitoring. 00, 44-49.
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chaired theses and dissertations
Email
mohamed.nounou@tamu.edu
First Name
Mohamed
Last Name
Nounou
mailing address
Texas A&M University; Qatar Campus; 4251 TAMUQ
College Station, TX 77843-4251
USA