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Design of big data anomaly detection model based on random forest algorithm
更新时间：2025-05-26

    • Design of big data anomaly detection model based on random forest algorithm

    • “In the field of big data anomaly detection, experts have proposed a model based on random forest algorithm, which effectively improves the detection accuracy, with an average accuracy of 91% and a false positive rate of 4.5%.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 53, Issue 9, Pages: 2659-2665(2023)
    • 作者机构：

      1.西南交通大学 交通运输与物流学院， 成都 610031

      2.西南交通大学 土木工程学院， 成都 610031

    • DOI：10.13229/j.cnki.jdxbgxb.20220598    

      CLC： TM714

    • Received：18 May 2022，

      Published：01 September 2023

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  • SONG Shi-jun,FAN Min.Design of big data anomaly detection model based on random forest algorithm[J].Journal of Jilin University(Engineering and Technology Edition),2023,53(09):2659-2665. DOI： 10.13229/j.cnki.jdxbgxb.20220598.

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