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Titlebook: Machine Learning for Cyber Security; 4th International Co Yuan Xu,Hongyang Yan,Jin Li Conference proceedings 2023 The Editor(s) (if applica

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樓主: Taylor
21#
發(fā)表于 2025-3-25 07:15:07 | 只看該作者
Botao Tu,Guanxiang Yin,Guoqing Zhong,Nan Jiang,Yuejin Zhang
22#
發(fā)表于 2025-3-25 10:41:47 | 只看該作者
Machine Learning Based Abnormal Flow Analysis of University Course Teaching Network,valuation and unknown traffic detection, the network traffic analysis steps are designed to analyze the abnormal situation of teaching network traffic. The experimental results show that the highest F1 score is 98%, and the accuracy of the analysis results is high, which provides sufficient network traffic for college course teaching.
23#
發(fā)表于 2025-3-25 15:44:34 | 只看該作者
,A Learned Multi-objective Bacterial Foraging Optimization Algorithm with?Continuous Deep Q-Learningadaptive parameter control. To verify the feasibility of LMBFO, it is trained and tested on classical multi-objective benchmark functions. Moreover, MBFO is utilized as the comparison to illustrate the superiority of our proposed MLBFO.
24#
發(fā)表于 2025-3-25 18:34:04 | 只看該作者
A Tabu-Based Multi-objective Particle Swarm Optimization for Irregular Flight Recovery Problem,le swarm optimization introducing the idea of tabu search. Thirdly, we devised an encoding scheme focusing on the characteristic of the problem. Finally, we verified the superiority of the tabu-based multi-objective particle swarm optimization through the comparison against MOPSO by the experiment based on real-world data.
25#
發(fā)表于 2025-3-25 22:34:49 | 只看該作者
26#
發(fā)表于 2025-3-26 01:12:29 | 只看該作者
27#
發(fā)表于 2025-3-26 08:15:10 | 只看該作者
28#
發(fā)表于 2025-3-26 11:41:12 | 只看該作者
Human Resource Network Information Recommendation Method Based on Machine Learning,combined with hybrid genetic algorithm. The experimental results show that the highest recommendation accuracy of this method reaches 94%, and the highest recall rate is 0.90, which indicates that the application of research methods to recommend human resources network information has a good effect.
29#
發(fā)表于 2025-3-26 16:23:53 | 只看該作者
30#
發(fā)表于 2025-3-26 17:39:06 | 只看該作者
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