💻 computer science

Research on Predictive Modelling of Volleyball Game Outcomes Using Machine Learning Techniques and Data Analytics

本文介绍了一项机器学习研究,该研究利用在合成数据上训练并在波兰排球超级联赛(PlusLiga)真实比赛上进行验证的梯度提升(Gradient Boosting)和随机森林(Random Forest)模型,成功预测了职业排球比赛结果,准确率超过93%,并确定了一传(OPI)和得分差(Break-Point Differentials)是关键的预测特征。

Xiaopeng Li2026-06-24
💻 computer science

AI-Driven Trust-Aware Security Enhancement Framework for Cognitive Radio Networks Against SSDF, PUE, and Jamming Attacks

本文提出了一种面向认知无线电网络的AI驱动信任感知安全框架,该框架集成了基于随机森林的检测与贝叶斯信任评估,以有效缓解恶意二次节点(SSDF)、伪用户枚举(PUE)及干扰攻击,在严苛的攻击条件和低信噪比水平下仍能实现高检测精度,并显著提升网络可靠性与吞吐量。

Joseph Wumboranaan NANJO, Kusi Ankrah Bonsu, Kwame Oteng Gyasi2026-06-24
💻 computer science

CATBridge: Enhancing CVE-ATT&CK Alignment Capability in Low-Resource Environments Using Professional Knowledge from LLMs

本文提出了 CATBridge,一种多阶段知识增强框架,该框架利用教师-学生协作机制来引导轻量级大语言模型在低资源环境下实现卓越的 CVE-ATT&CK 对齐准确率,其性能显著优于现有的最先进方法以及零样本大规模模型。

Maomiao Xiao, Hao Hu, Yingchang Jiang, Yichen Li, Jianxiao Yu, Feiyang Li, Yuling Liu, Yuchen Zhang2026-06-24