Data-driven methods for power converter fault diagnosis
This Final Year Project (FYP) report investigates the efficacy of data-driven methods for power converter fault analysis, employing three distinct algorithms: Extreme Learning Machine (ELM), Random Vector Functional Link (RVFL), and Random Forest. The study aims to assess the performance of these al...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/176909 |
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| Institution: | Nanyang Technological University |
| Language: | English |