Laser Journal, Volume. 45, Issue 1, 179(2024)

Automatic identification method of abnormal traffic in elastic optical network based on isolated forest algorithm

LI Cheng1,*... HE Sunqin2, WEI Xing1 and ZHANG Guohua1 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
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    References(5)

    [11] [11] Ahn D, Kim S, Kim S, et al. Wireless power transfer receiver with adjustable coil output voltage for multiple receivers application[J]. IEEE Transactions on Industrial Electronics,2019, 66(5):4003-4012.

    [12] [12] Pandiyan V, Prost J, Vorlaufer G, et al. Identification of abnormal tribological regimes using a microphone and semisupervised machine-learning algorithm[J]. 2022,4:108-117.

    [13] [13] Cheng J, Ma F, Envelope J W, et al. Early Identification of Abnormal Deviations in Nonstationary Processes by Removing Non- Stationarity[J]. Computer Aided Chemical Engineering, 2022, 49:1393-1398.

    [14] [14] Wei J, Ma Q, Wang W, et al. Abnormal area identification of corn ear based on semi-supervised learning[J]. IET image processing, 2022(9):16.

    [15] [15] Jing X Y, Yan Z, Pedrycz W. Security data collection and data analytics in the Internet: a survey[J]. IEEE Communications Surveys and Tutorials, 2019, 21(1): 586-618.

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    LI Cheng, HE Sunqin, WEI Xing, ZHANG Guohua. Automatic identification method of abnormal traffic in elastic optical network based on isolated forest algorithm[J]. Laser Journal, 2024, 45(1): 179

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    Paper Information

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    Received: Apr. 21, 2023

    Accepted: --

    Published Online: Aug. 6, 2024

    The Author Email: Cheng LI (dingdoudou201310@163.com)

    DOI:10.14016/j.cnki.jgzz.2024.1.179

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