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Depot Institutionnel de l'UMBB >
Browsing by Subject Random forest
Showing results 1 to 6 of 6
| Date de publication | Titre | Auteur(s) | | 2025 | Analysis of bearings defaults using machine learning techniques | Moussaoui, Imane; Benazzouz, Djamel(Directeur de thèse) |
| 2024 | Computerized diagnosis of knee osteoarthritis from x-ray images using combined texture features: Data from the osteoarthritis initiative | Messaoudene, Khadidja; Harrar, Khaled |
| 2021 | Detection of knee osteoarthritis based on wavelet and random forest model | Messaoudene, Khadidja; Harrar, Khaled |
| 2023 | Enhancing fault diagnosis of undesirable events in oil & gas systems: A machine learning approach with new criteria for stability analysis and classification accuracy | Sahraoui, Mohammed Amine; Rahmoune, Chemseddine; Zair, Mohamed; Gougam, Fawzi; Damou, Ali |
| 2023 | Rolling bearing fault feature selection based on standard deviation and random forest classifier using vibration signals | Moussaoui, Imane; Rahmoune, Chemseddine; Benazzouz, Djamel |
| 2021 | Topological analysis for osteoporosis assessment in X-Ray images using random forest model | Harrar, Khaled |
Showing results 1 to 6 of 6
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