Jaouher Ben Ali
Orcid: 0000-0002-3137-2865
According to our database1,
Jaouher Ben Ali
authored at least 14 papers
between 2014 and 2024.
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Bibliography
2024
Proceedings of the 10th International Conference on Control, 2024
MOSFET Remaining Useful Life Prediction Using Long Short-Term Memory Artificial Neural Network.
Proceedings of the 10th International Conference on Control, 2024
2023
Reliable state of health condition monitoring of Li-ion batteries based on incremental support vector regression with parameters optimization.
J. Syst. Control. Eng., April, 2023
Polyneuropathy Early Detection Based on Electrodermal Activity Features and Support Vector Machines.
Proceedings of the 9th International Conference on Control, 2023
2019
A New Adaptive Prognostic Strategy Based on Online Future Evaluation and Extended Kalman Filtering.
Proceedings of the 6th International Conference on Control, 2019
2018
A new suitable feature selection and regression procedure for lithium-ion battery prognostics.
Int. J. Comput. Appl. Technol., 2018
Fast unsupervised nuclear segmentation and classification scheme for automatic allred cancer scoring in immunohistochemical breast tissue images.
Comput. Methods Programs Biomed., 2018
Wind turbine drivetrain prognosis approach based on Kalman smoother with confidence bounds.
Proceedings of the IEEE International Conference on Industrial Technology, 2018
Proceedings of the 5th International Conference on Control, 2018
2017
Particle filter-based prognostic approach for high-speed shaft bearing wind turbine progressive degradations.
Proceedings of the IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, Beijing, China, October 29, 2017
Proceedings of the International Conference on Control, Automation and Diagnosis, 2017
2015
Linear feature selection and classification using PNN and SFAM neural networks for a nearly online diagnosis of bearing naturally progressing degradations.
Eng. Appl. Artif. Intell., 2015
2014
Neurocomputing, 2014
Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis.
Proceedings of the 6th International Conference of Soft Computing and Pattern Recognition, 2014