Research Article
Feature Extraction and Classification of Power Quality Disturbances Using Optimized Tunable-Q Wavelet Transform and Incremental Support Vector Machine
Table 13
Statistics comparing the accuracy of other common methods.
| Methods of classification | Accuracy percentage (50 dB noise addition) |
| ANN-based DWT | 94.37 | NFS-based DWT | 96.5 | MSVM-based WPT | 96.8 | RBES-based DWT | 98.7 | DT-based ST | 98.5 | RBES-based ST | 98.2 | PNN-based ST | 97.4 | ST with FES-CF | 99.8 | Proposed OTQWT with ISVM | 99.64 |
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