Okba Taouali

Orcid: 0000-0003-4610-7885

According to our database1, Okba Taouali authored at least 28 papers between 2009 and 2024.

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

Timeline

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Bibliography

2024
Anomaly-based intrusion detection system in IoT using kernel extreme learning machine.
J. Ambient Intell. Humaniz. Comput., January, 2024

A Deep-Learning-Integrated Blockchain Framework for Securing Industrial IoT.
IEEE Internet Things J., 2024

2023
Anomaly detection for process monitoring based on machine learning technique.
Neural Comput. Appl., February, 2023

Intelligent Intrusion Detection System for the Internet of Medical Things Based on Data-Driven Techniques.
Comput. Syst. Sci. Eng., 2023

2022
Early detection of digital mammogram using kernel extreme learning machine.
Concurr. Comput. Pract. Exp., 2022

2021
An enhanced CAD system based on machine Learning Algorithm for brain MRI classification.
J. Intell. Fuzzy Syst., 2021

An Improved Fault Diagnosis Strategy for Process Monitoring Using Reconstruction Based Contributions.
IEEE Access, 2021

Uncertain Dynamic Process Monitoring Using Moving Window Interval PCA.
Proceedings of the 18th International Multi-Conference on Systems, Signals & Devices, 2021

2020
Machine learning technique for data-driven fault detection of nonlinear processes.
J. Intell. Manuf., 2020

Enhanced SVM-KPCA Method for Brain MR Image Classification.
Comput. J., 2020

2019
New online kernel method with the Tabu search algorithm for process monitoring.
Trans. Inst. Meas. Control, 2019

An improved machine learning technique based on downsized KPCA for Alzheimer's disease classification.
Int. J. Imaging Syst. Technol., 2019

New kernel method for MRI classification.
Proceedings of the 16th International Multi-Conference on Systems, Signals & Devices, 2019

2018
Fault detection and isolation in nonlinear systems with partial Reduced Kernel Principal Component Analysis method.
Trans. Inst. Meas. Control, 2018

Reduced Kernel Principal Component Analysis for Fault Detection and Its Application to an Air Quality Monitoring Network.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Fault Detection of the Tennessee Eastman Process using Online Reduced Kernel PCA.
Proceedings of the 16th European Control Conference, 2018

Fault Diagnosis for Dynamic Nonlinear System Based on Variable Moving Window KPCA.
Proceedings of the 15th International Multi-Conference on Systems, Signals & Devices, 2018

2017
Fault detection localization and reconstruction in nonlinear system using RKPCA method and RBC.
Proceedings of the International Conference on Control, Automation and Diagnosis, 2017

Online process monitoring based on kernel method.
Proceedings of the International Conference on Control, Automation and Diagnosis, 2017

2016
Identification of nonlinear systems with kernel methods.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016

2015
Online identification of nonlinear system using a new kernel algorithm.
Proceedings of the 4th International Conference on Systems and Control, 2015

On the application of recursive principal component analysis method to fault detection and isolation.
Proceedings of the 4th International Conference on Systems and Control, 2015

2014
Hybrid kernel identification method based on support vector regression and regularisation network algorithms.
IET Signal Process., 2014

2013
A new online fault detection method based on PCA technique.
IMA J. Math. Control. Inf., 2013

2012
Online identification of nonlinear system using reduced kernel principal component analysis.
Neural Comput. Appl., 2012

Design and comparative study of online kernel methods identification of nonlinear system in RKHS space.
Artif. Intell. Rev., 2012

2009
A comparative study of non linear MISO Process modelling techniques: Application to a chemical reactor.
Proceedings of the 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing, 2009

Identification of non linear multivariable processes modelled on reproducing Kernel Hilbert space: Application to Tennessee process.
Proceedings of the 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing, 2009


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