An Improved Detection System Using Genetic Algorithm and Decision Tree
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-61929-8_8
Reference15 articles.
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2. Shen, H., et al.: Counterfeit anomaly using generative adversarial network for anomaly detection. IEEE Access 8, 133051–133062 (2020)
3. Shajari, M., Geng, H., Kaixuan, H., Leon-Garcia, A.: Tensor-based online network anomaly detection and diagnosis. IEEE Access 10, 85792–85817 (2022). https://doi.org/10.1109/ACCESS.2022.3197651
4. Kim, H., Lee, B.S., Shin, W.-Y., Lim, S.: Graph anomaly detection with graph neural networks: current status and challenges. IEEE Access 10, 111820–111829 (2022). https://doi.org/10.1109/ACCESS.2022.3211306
5. Lundström, A., et al.: Improving deep learning based anomaly detection on multivariate time series through separated anomaly scoring. IEEE Access 10, 108194–108204 (2022)
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