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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 |
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