Jaouher Ben Ali

Orcid: 0000-0002-3137-2865

According to our database1, Jaouher Ben Ali authored at least 12 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

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

Direct Wind Turbine Drivetrain Prognosis Approach Using Elman Neural Network.
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

State of health estimation of lithium-ion batteries based on regression techniques.
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
Identification of early-stage Alzheimer's disease using SFAM neural network.
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


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