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DGMSCL:一种动态图混合监督对比学习方法,用于类不平衡的多变量时间序列分类.

Lipeng Qian1, Qiong Zuo1, Dahu Li2

  • 1School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430070, Hubei, China.

Neural networks : the official journal of the International Neural Network Society
|January 25, 2025
PubMed
概括

本研究介绍了一种基于动态图的方法,用于不平衡的多变量时间序列分类. 该方法通过改进特征表示和对比学习来增强对关键少数类事件的检测.

关键词:
类不平衡的多变量时间序列分类.动态图表的动态图表层次关注图表神经网络的神经网络.混合的对比学习学习.

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