The XGBoost Model for Network Intrusion Detection Boosted by Enhanced Sine Cosine Algorithm-Reference-Cited by-同舟云学术

The XGBoost Model for Network Intrusion Detection Boosted by Enhanced Sine Cosine Algorithm

Published:2022 Issue: Volume: Page:213-228
ISSN:2367-3370
Container-title:Third International Conference on Image Processing and Capsule Networks
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Author:

AlHosni Nadheera^ORCID,Jovanovic Luka^ORCID,Antonijevic Milos^ORCID,Bukumira Milos^ORCID,Zivkovic Miodrag^ORCID,Strumberger Ivana^ORCID,Mani Joseph P.^ORCID,Bacanin Nebojsa^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-12413-6_17

Reference51 articles.

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2. Anderson, J.A.: An Introduction to Neural Networks. MIT Press, Cambridge (1995)

3. Bacanin, N., Alhazmi, K., Zivkovic, M., Venkatachalam, K., Bezdan, T., Nebhen, J.: Training multi-layer perceptron with enhanced brain storm optimization metaheuristics. Comput. Mater. Continua 70(2), 4199–4215 (2022). https://doi.org/10.32604/cmc.2022.020449, http://www.techscience.com/cmc/v70n2/44706

4. Lecture Notes on Data Engineering and Communications Technologies;N Bacanin,2022

5. Bacanin, N., Bezdan, T., Tuba, E., Strumberger, I., Tuba, M.: Monarch butterfly optimization based convolutional neural network design. Mathematics 8(6), 936 (2020)

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