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Intrusion detection method based on ensemble learning and feature selection by PSO-GA
更新时间：2025-07-22

    • Intrusion detection method based on ensemble learning and feature selection by PSO-GA

    • “In the field of industrial network security, experts have proposed a new intrusion detection method that extracts features through a particle swarm optimization genetic hybrid algorithm and improves prediction accuracy using a stacked ensemble learning framework, achieving detection accuracies of 95% and 93%, respectively.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 55, Issue 4, Pages: 1396-1405(2025)
    • 作者机构：

      沈阳化工大学 计算机科学与技术学院，沈阳 110142

    • DOI：10.13229/j.cnki.jdxbgxb.20230751    

      CLC： TP399

    • Received：17 July 2023，

      Published：01 April 2025

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  • WANG Jun,SI Chang-fu,WANG Kai-peng,et al.Intrusion detection method based on ensemble learning and feature selection by PSO-GA[J].Journal of Jilin University(Engineering and Technology Edition),2025,55(04):1396-1405. DOI： 10.13229/j.cnki.jdxbgxb.20230751.

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