【摘要】 前兆观测数据真实可靠地应用在地震预测中前提是观测人员能够准确去除和标记干扰异常数据。为了能够在前兆数据预处理过程中由计算机及时检测出异常值,文章在时间序列的异常值检测的基础上,提出一套前兆仪器数据异常判定方法。根据异常的特征分析,首先选取合适的阈值特征进行阈值异常检测,在阈值异常检测结果的基础上,进而将其与邻近观测点数据进行相似性度量。从而达到将局部干扰异常与地球物理变化区分的目的。这种异常判定规则应用在前兆预处理中大大提高了前兆数据预处理的准确性和效率。同时,这种异常判定规则应用在实时监控中可以及时发现仪器的故障以及解决异常数据隐蔽性和时效性的问题。更多还原

【Abstract】 Pretreatment able to accurately remove Abnormal interference data is the premise of Precursor observation data applied in earthquake prediction reliably.in order to detect outliers in the process of precursory data pretreatment,based on the time series outlier detection,put forward a set of method for judging abnormal According to the analysis of abnormal characteristics,abnormality judging rules are divided into user defined threshold rules and similarity measure rule.and then were given two types of abnormal decision algorithm.First of all,Select suitable threshold characteristics for anomaly detection,on the basis of the result of threshold outlier detection,Then,process similarity measurement with the data of the adjacent observation point.So as to achieve the purpose of making a distinction between local disturbance and geophysical changes.更多还原