Partial faults features.

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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Bibliographic Details
Main Author: Ning Ji (325849) (author)
Other Authors: Xi Chen (35903) (author), Xue Qin (123365) (author), Wei Wei (21173) (author), Chenlu Jiang (19959475) (author), Yifan Bo (16324032) (author), Kai Tao (54204) (author)
Published: 2024
Subjects:
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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