Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Hanen Chaouch"'
Publikováno v:
Mathematics, Vol 10, Iss 6, p 890 (2022)
In this study, a multiscale monitoring method for nonlinear processes was developed. We introduced a machine learning tool for fault detection and isolation based on the kernel principal component analysis (PCA) and discrete wavelet transform. The pr
Externí odkaz:
https://doaj.org/article/2f8bd749738c48b0a9317fb757f71b62
Publikováno v:
Neural Computing and Applications. 31:1153-1163
This paper is mainly aimed at developing an off-line supervision approach geared to complex processes. This approach consists of two parts: the first part is the fault detection and isolation and the second one is the process control. The first part
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9482717a1c834969bee807f949c67047
https://doi.org/10.1007/s00521-017-3147-9
https://doi.org/10.1007/s00521-017-3147-9
Multi-variable process data compression and defect isolation using wavelet PCA and genetic algorithm
Publikováno v:
The International Journal of Advanced Manufacturing Technology. 91:869-878
This paper characterizes an approach to data compression and defect isolation for the multi-variable process by introducing the wavelet principal component analysis (PCA) and the genetic algorithms. In the defect analysis process, data compression is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77373d7b76383e6928e6a7115957a74e
https://doi.org/10.1007/s00170-016-9774-y
https://doi.org/10.1007/s00170-016-9774-y
Publikováno v:
The International Journal of Advanced Manufacturing Technology. 87:1183-1191
The major goal of this paper is the description of a fault detection and isolation system. Such a system is geared to the complex processes through the combination of the neural networks, Fisher discriminate analysis and the principal component analy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2fad64b71298e566bddd9d54e5f848e
https://doi.org/10.1007/s00170-016-8549-9
https://doi.org/10.1007/s00170-016-8549-9
Publikováno v:
2017 International Conference on Engineering & MIS (ICEMIS).
This paper proposes a monitoring and regulation approach by combining main component analysis and fuzzy logic. This approach is applied to a motorway history of four variables: traffic density, flow rate, average speed and occupancy rate, and 900 obs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63cf1d3a08e3343104dd9d368d99d45c
https://doi.org/10.1109/icemis.2017.8273088
https://doi.org/10.1109/icemis.2017.8273088
Autor:
Hanen Chaouch
Publikováno v:
2017 International Conference on Engineering & MIS (ICEMIS).
In this paper, a study of the regularity of the electrocardiogram is given by the integration of a process diagnostic tool that is kernel principal components. It is a question of detecting the defects which exist in the set of parameters of the proc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14c8749c67b004f9d2c161820326419c
https://doi.org/10.1109/icemis.2017.8273087
https://doi.org/10.1109/icemis.2017.8273087
Publikováno v:
2017 International Conference on Control, Automation and Diagnosis (ICCAD).
This This paper describes a proposed monitoring approach destined for industrial process using the principal components analysis (PCA) and fuzzy logic. The aim of our work is to detect and locate defaults using PCA and then classifying the existed pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a4c26310480db6ccb31524fc4ec3ce1
https://doi.org/10.1109/cadiag.2017.8075688
https://doi.org/10.1109/cadiag.2017.8075688
Publikováno v:
2017 International Conference on Control, Automation and Diagnosis (ICCAD).
This paper deals with a detection approach that tries to solve major problems of traffic flow by combining a higher order modeling tool and the principal components analysis. This modeling system is applied to the data preprocessing level. The PCA is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c24751f7936f4b5b8a465793d8fc8751
https://doi.org/10.1109/cadiag.2017.8075689
https://doi.org/10.1109/cadiag.2017.8075689
Publikováno v:
International Journal of Biomedical Engineering and Technology. 26:1
In this paper, a statistical method of ECG analysis and diagnostic is proposed. This method is based on three parts: data simplification using multiscaled PCA, faults detection and localisation by introducing classic linear PCA. The studied data is p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4963c57edff537744708870668f29cd8
https://doi.org/10.1504/ijbet.2018.089244
https://doi.org/10.1504/ijbet.2018.089244
Publikováno v:
International Journal of Modelling, Identification and Control. 27:68
In this paper, we propose a new method based on multiscaled principal component analysis for nonlinear systems analysis. We introduce nonlinear PCA based on neural networks and discrete wavelet transform. The data matrix describing a nonlinear proces
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::490d680b921d8639a7b42cf852adcea0
https://doi.org/10.1504/ijmic.2017.10003316
https://doi.org/10.1504/ijmic.2017.10003316