闫伟, 王海涛. 2019: 利用动态时间规整方法实现不同时间长度地震观测资料的形态匹配. 地震学报, 41(6): 769-777. DOI: 10.11939/jass.20190016
引用本文: 闫伟, 王海涛. 2019: 利用动态时间规整方法实现不同时间长度地震观测资料的形态匹配. 地震学报, 41(6): 769-777. DOI: 10.11939/jass.20190016
Yan Wei, Wang Haitao. 2019: Morphological matching of seismic observation date with different time length using dynamic time warping method. Acta Seismologica Sinica, 41(6): 769-777. DOI: 10.11939/jass.20190016
Citation: Yan Wei, Wang Haitao. 2019: Morphological matching of seismic observation date with different time length using dynamic time warping method. Acta Seismologica Sinica, 41(6): 769-777. DOI: 10.11939/jass.20190016

利用动态时间规整方法实现不同时间长度地震观测资料的形态匹配

Morphological matching of seismic observation date with different time length using dynamic time warping method

  • 摘要: 本文将动态时间规整方法引入到地震观测资料的形态匹配分析中,以解决因时间尺度不一致的两列观测数据无法定量比对的问题。基于动态时间规整技术方法原理,通过测试数据验证了动态时间规整方法的可行性,并利用云南西部地区的断层实际观测数据,分析了1996年丽江MS7.0地震前的跨断层观测数据异常形态与当前数据异常形态的相似性问题。结果表明:① 动态时间规整方法可用于地震资料时间长度不一致时的相似性匹配;② 时间不一致的两列观测数据可用累积规整路径距离来定量表征,累积距离越短,曲线形态越一致;③ 动态时间规整方法可用于给定模板的前兆数据相似度的计算机自动提取,可提高当前仅依靠人工判别的工作效率;④ 从模式识别的角度考虑,当前下关跨断层水准观测数据变化形态与1996年丽江MS7.0地震和2008年汶川MS8.0地震前的水准数据变化形态较为一致。

     

    Abstract: In this paper, the dynamic time warping (DTW) method is introduced so as to solve the problem that the two observation data cannot be compared due to their different time length. On the basis of the principle of dynamic time warping technology, this paper verifies the feasi-bility of identifying the conformity of seismic observation data by testing sample data. At the same time, using the actual fault observation data in western Yunnan, the similarity between the anomalous morphology before the 1996 Lijiang MS7.0 earthquake and the current anomalous morphology is studied. The results show that: ① The DTW algorithm can be used for similarity matching of precursor data in seismological field; ② Time-inconsistent precursor observation data can be expressed by cumulative warping distance, the shorter the cumulative distance, the more consistent the curve shape; ③ The DTW algorithm can be used for automatic extraction of precursor data similarity of template-making, which can improve the current work efficiency in the case of only relying on manual tracking precursor curve changes; ④ Considering from the point of view of pattern recognition, the data of Xiaguan  cross-fault leveling are consistent with those before Lijiang MS7.0 earthquake in 1996 and Wenchuan MS8.0 earthquake in 2008.

     

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