Partial faults features.

<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. First, a Dual-channel model is cons...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ning Ji (325849) (author)
مؤلفون آخرون:	Xi Chen (35903) (author), Xue Qin (123365) (author), Wei Wei (21173) (author), Chenlu Jiang (19959475) (author), Yifan Bo (16324032) (author), Kai Tao (54204) (author)
منشور في:	2024
الموضوعات:	Medicine Biotechnology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified simulated using ddrts digital dynamic real 6 %, 9 1 %, 9 identification method based typical transformer faults 3 %- 96 proposed method improved method </ p transformer faults 3 %, proposed method optimized method xlink "> time simulator result indicates inspired algorithms hidden layer experiments showed attention model attention mechanism
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Partial faults features.

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