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https://di.univ-blida.dz/jspui/handle/123456789/25194
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Élément Dublin Core | Valeur | Langue |
---|---|---|
dc.contributor.author | ZERMANE, Ali | - |
dc.contributor.author | BERANA, Ayoub | - |
dc.date.accessioned | 2023-10-04T09:16:52Z | - |
dc.date.available | 2023-10-04T09:16:52Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | https://di.univ-blida.dz/jspui/handle/123456789/25194 | - |
dc.description | 4.629.1.150/ p61 | fr_FR |
dc.description.abstract | Bee colony optimization algorithms are increasingly being used for solving certain optimization problems. This study aims to implement an Artificial Bee Colony (ABC) algorithm for asynchronous machine identification and compare its performance with the traditional identification method The results obtained from the traditional method are improved using the ABC algorithm, considering mean squared error as the performance criterion. Tests were conducted, which demonstrated the superiority and efficiency of the ABC method in terms of minimizing this error and determining the parameters of the asynchronous machine compared to the traditional methods. | fr_FR |
dc.language.iso | fr | fr_FR |
dc.publisher | blida 1 | fr_FR |
dc.subject | asynchronous machine, Bee Colony algorithm, classical experiments, MAS parameter identification. | fr_FR |
dc.title | Identification paramétrique de la machine asynchrone par la méthode de colonie d’abeille artificielle | fr_FR |
dc.type | Other | fr_FR |
Collection(s) : | Mémoires de Master |
Fichier(s) constituant ce document :
Fichier | Description | Taille | Format | |
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NSHLH FINAL 2023.pdf | 3,16 MB | Adobe PDF | Voir/Ouvrir |
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