Table 3 Optimal weighted feature selection performance of the implemented scheme in aquaponic Fish Ponds among conventional algorithms.
Metrics | RNN24 | LSTM23 | CA27 | GRU28 | MSCA-GRU |
|---|---|---|---|---|---|
Accuracy | 90.03539 | 88.54764 | 91.46837 | 91.73136 | 94.03911 |
Recall | 90.04911 | 88.54544 | 91.46623 | 91.73221 | 94.03606 |
Specificity | 90.01266 | 88.5513 | 91.47193 | 91.72994 | 94.04417 |
Precision | 93.72837 | 92.76384 | 94.67448 | 94.84149 | 96.31954 |
FPR | 9.987336 | 11.4487 | 8.528069 | 8.270056 | 5.955828 |
FNR | 9.950892 | 11.45456 | 8.533775 | 8.267788 | 5.963941 |
NPV | 84.51375 | 82.34455 | 86.60729 | 87.00222 | 90.48837 |
FDR | 6.271634 | 7.236163 | 5.325523 | 5.158512 | 3.680456 |
F1-Score | 91.85191 | 90.60557 | 93.0427 | 93.26094 | 95.16411 |
MCC | 0.791467 | 0.760961 | 0.821058 | 0.82649 | 0.874418 |
Accuracy | 90.03539 | 88.54764 | 91.46837 | 91.73136 | 94.03911 |
