Research Article
An Improved Power Quality Disturbance Detection Using Deep Learning Approach
Table 7
Evaluation parameters of the three models.
| | Actual | CNN + LSTM | CNN + GRU | DCNN | | Precision | Recall | F1 score | Precision | Recall | F1 score | Precision | Recall | F1 score |
| | C1 | 1.0000 | 0.9902 | 0.9951 | 0.9868 | 0.9901 | 0.9885 | 0.9868 | 0.9901 | 0.9885 | | C2 | 0.9938 | 1.0000 | 0.9969 | 0.9938 | 1.0000 | 0.9969 | 0.9938 | 1.0000 | 0.9969 | | C3 | 0.9902 | 1.0000 | 0.9951 | 0.9935 | 0.9902 | 0.9918 | 0.9935 | 0.9902 | 0.9918 | | C4 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | | C5 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | | C6 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | | C7 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | | C8 | 1.0000 | 0.9971 | 0.9986 | 1.0000 | 0.9971 | 0.9986 | 1.0000 | 0.9971 | 0.9986 | | C9 | 1.0000 | 1.0000 | 1.0000 | 0.9971 | 0.9971 | 0.9971 | 0.9971 | 0.9971 | 0.9971 | | C10 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 0.9967 | 0.9984 | 1.0000 | 0.9967 | 0.9984 | | C11 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | | C12 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | | C13 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 0.9968 | 1.0000 | 0.9984 | | C14 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 0.9936 | 0.9968 | 0.9968 | 0.9936 | 0.9952 | | C15 | 1.0000 | 1.0000 | 1.0000 | 0.9945 | 1.0000 | 0.9972 | 0.9945 | 0.9917 | 0.9931 | | C16 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 0.9939 | 0.9970 | 0.9954 | | Average | 0.9990 | 0.9992 | 0.9991 | 0.9979 | 0.9978 | 0.9978 | 0.9971 | 0.9971 | 0.9971 |
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