Power quality disturbance classification using deep BiLSTM architectures with exponentially decayed number of nodes in the hidden layers
In recent years, there is growing interest in automatic power quality disturbance (PQD) classification using deep learning algorithms. In this paper, the average of instantaneous frequency and the average of spectrum entropy were used as time-frequency based feature extraction due to its discriminat...
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| Main Authors: | , , , |
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| Format: | Book Chapter |
| Language: | en en |
| Published: |
Springer
2020
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/84769/2/Gunawan_im3f_65.pdf http://irep.iium.edu.my/84769/1/Acceptance%20Letter_DrTeddy_IIUM.pdf http://irep.iium.edu.my/84769/ https://im3f2020.ump.edu.my/index.php/en/ |
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