Application of symmetric uncertainty and emperor penguin–grey wolf optimisation for feature selection in motor fault classification
Abstract The authors present a model for diagnosing motor faults based on machine learning, demonstrating advantages over other algorithms in terms of both improved fitness values and reduced running time. The structure of the model involves three primary phases: feature extraction, feature selectio...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-10-01
|
| Series: | IET Electric Power Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/elp2.12459 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|