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差异区域平衡法探索时间序列变化的因果关系

王开军 曾元鹏 缪忠剑

王开军, 曾元鹏, 缪忠剑. 差异区域平衡法探索时间序列变化的因果关系[J]. 电子与信息学报, 2021, 43(8): 2414-2420. doi: 10.11999/JEIT200756
引用本文: 王开军, 曾元鹏, 缪忠剑. 差异区域平衡法探索时间序列变化的因果关系[J]. 电子与信息学报, 2021, 43(8): 2414-2420. doi: 10.11999/JEIT200756
Kaijun WANG, Yuanpeng ZENG, Zhongjian MIAO. Different-region Balance Method for Exploring Varying Causal Relations Between Time Series[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2414-2420. doi: 10.11999/JEIT200756
Citation: Kaijun WANG, Yuanpeng ZENG, Zhongjian MIAO. Different-region Balance Method for Exploring Varying Causal Relations Between Time Series[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2414-2420. doi: 10.11999/JEIT200756

差异区域平衡法探索时间序列变化的因果关系

doi: 10.11999/JEIT200756
基金项目: 国家自然科学基金(61672157),福建省自然科学基金 (2018J01778)
详细信息
    作者简介:

    王开军:男,1965年生,副教授,研究方向为机器学习和数据挖掘

    曾元鹏:男,1995年生,硕士生,研究方向为模式识别和数据挖掘

    通讯作者:

    王开军 wkjwang@qq.com

  • 中图分类号: TP391.4

Different-region Balance Method for Exploring Varying Causal Relations Between Time Series

Funds: The National Natural Science Foundation of China (61672157), The Natural Science Foundation of Fujian Province (2018J01778)
  • 摘要: 针对探索时间序列之间随时间变化的因果关系问题,在每个窗口进行Granger因果检测的滑动时间窗口方法是求解该问题的常用方法,但其性能对窗宽敏感,不合适的窗宽很可能导致低性能。该文提出一种差异区域平衡方法,首先计算当前滑动窗口W内序列的波动程度Sw并作为波动界,计算窗口W的前向相邻区域U内序列的波动程度Su。然后,实施前向探索策略:若Su未超过Sw,则实施不同长度区域的平衡检测方案,即对窗口W、对窗口W与U的合并区域、对窗口W与后向相邻区域V的合并区域这3种不同长度的差异区域,分别进行时间序列之间因果关系的检测;若Su超过Sw,则实施上述平衡检测方案时,其中区域U和V的长度取相同值。最后,将窗口W的多次检测结果进行综合后输出。新方法将不同长度区域的结果进行综合,能够降低方法的性能对窗宽的敏感性,保障最终结果的准确性和稳定性。在1个模拟数据集和4个真实数据集上的实验结果显示,该文方法能有效地揭示出时间序列之间随时间变化的因果关系,在正确率高且性能稳定的综合性能上优于对比方法。
  • 图  1  两条序列的有近似线性关系区域[t1, t2]和无线性关系区域[t2, t7]

    表  1  不同方法在模拟数据集上发掘因果关系的正确率(%)

    窗口宽度滑动步长噪声方差0.01噪声方差0.2噪声方差0.5
    常规F界转折平衡常规F界转折平衡常规F界转折平衡
    20591.3288.1890.9995.4080.8294.565884.1380.5791.0050.2982.52
    1088.9888.1891.9195.0680.2594.5653.3983.3380.1591.0046.3382.54
    1586.7888.1890.0094.4378.194.5644.8683.2678.5291.0046.2282.03
    2083.6588.1889.1792.7777.0594.5645.482.1577.9891.0045.4881.87
    30595.8588.1890.6195.8785.6994.5660.492.3183.6391.0047.3787.78
    1094.4388.1890.1595.4984.9594.5653.0191.9583.6991.0046.487.41
    1594.0788.1890.8594.9183.2294.5651.6291.6581.9391.0045.9886.84
    2092.9688.1890.9595.5781.6294.5653.2191.3781.1891.0046.3886.96
    40595.5688.1891.8394.8592.4694.5663.5294.6587.6291.0046.4392.17
    1095.3188.1890.0794.8791.0594.5658.8994.2787.0891.0045.3892.22
    1594.9588.1890.6594.7790.6294.5658.7794.5586.8791.0046.3991.76
    2094.5988.1889.994.3189.594.5652.3193.9385.8691.0045.8091.03
    下载: 导出CSV

    表  2  在数据集Dropoff-tweet上发掘因果关系的正确率(%)

    窗口
    宽度
    滑动
    步长
    常规滑
    动窗
    F界检测法转折点法差异平衡法
    12491.9592.6293.5693.42
    890.8792.6293.5693.83
    1289.2692.6294.3690.20
    18494.0992.6294.9095.30
    894.3692.6294.3694.77
    1292.2192.6294.3694.77
    24494.3692.6294.0996.51
    897.0592.6296.2496.78
    1291.9592.6291.4195.70
    下载: 导出CSV

    表  3  在数据集Tweet-pickup上发掘因果关系的正确率(%)

    窗口
    宽度
    滑动
    步长
    常规滑
    动窗
    F界检测法转折点法差异平衡法
    12490.8794.9090.8793.29
    891.9594.9094.0994.09
    1292.4894.9094.0991.01
    18492.4894.9088.1994.90
    892.4894.9093.8394.90
    1293.0294.9094.0993.02
    24492.7594.9091.4195.44
    893.2994.9082.8295.97
    1292.2194.9095.4495.44
    下载: 导出CSV

    表  4  在数据集Fish-school上发掘因果关系的正确率(%)

    窗口
    宽度
    滑动
    步长
    常规滑动窗F界检测法转折点法差异平衡法
    1401089.6054.1969.8090.1
    2086.2454.1969.8093.29
    3091.2854.1969.8095.64
    1501089.6054.1969.8084.90
    2083.2254.1969.8091.28
    3089.9354.1969.8099.66
    1601083.2254.1969.8086.91
    2069.8054.1969.8093.62
    3081.5454.1969.8092.95
    下载: 导出CSV

    表  5  在数据集Baboon-troop上发掘因果关系的正确率(%)

    窗口
    宽度
    滑动
    步长
    常规滑动窗F界检测法转折点法差异平衡法
    1101080.6335.3959.1080.63
    2070.6235.3959.1082.30
    3070.6235.3959.1080.47
    1201080.6335.3959.1081.64
    2062.2735.3959.1083.31
    3063.9435.3959.1083.97
    1301080.8035.3959.1082.30
    2075.7935.3959.1083.97
    3082.3035.3959.1082.97
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-08-26
  • 修回日期:  2021-01-01
  • 网络出版日期:  2021-01-07
  • 刊出日期:  2021-08-10

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