Research Article
Network Traffic Anomaly Detection Model Based on Feature Reduction and Bidirectional LSTM Neural Network Optimization
Table 6
Average running time of each algorithm.
| | PSOBSA | FOPSO | HPSO | ASPSO | OLPSO | GEPSO | HMaPSO | APPSO |
| F1 | 39.01 | 27.65 | 27.79 | 28.29 | 32.18 | 26.27 | 25.72 | 24.61 | F2 | 55.44 | 40.95 | 42.38 | 40.13 | 48.14 | 38.09 | 37.29 | 35.68 | F3 | 46.23 | 28.63 | 32.12 | 29.62 | 37.13 | 27.21 | 26.63 | 25.48 | F4 | 61.59 | 46.42 | 47.37 | 45.82 | 53.03 | 43.52 | 42.61 | 40.78 | F5 | 37.17 | 22.87 | 23.16 | 21.04 | 29.68 | 19.99 | 19.57 | 18.73 | F6 | 43.00 | 28.19 | 30.42 | 27.79 | 37.54 | 26.40 | 25.84 | 24.73 | F7 | 44.95 | 30.84 | 32.38 | 30.36 | 39.79 | 28.84 | 28.23 | 27.02 | F8 | 47.72 | 31.59 | 31.61 | 29.51 | 40.34 | 28.04 | 27.45 | 26.27 |
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