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System and method for detecting outliers in real time for univariate time series signals

机译:用于单变量时间序列信号的实时检测离群值的系统和方法

摘要

Disclosed is a method and system for detecting outliers in real-time for a univariate time-series signal. The system may receive the univariate time-series signal, comprising a plurality of datasets, from a data source. The system may compute a standard deviation of a dataset of the plurality of datasets. Subsequently, the system may compute the optimal sample block size and the critical sample size of the dataset. Further, the system may determine the optimal operational block size of the dataset. The system may segment the plurality of datasets into blocks based upon the optimal operational block size. The system may detect the outliers by performing an outlier detection technique on the blocks, thereby ensuring improved execution time while minimally affecting precision and accuracy of the outcome of the outlier detection method.
机译:公开了一种用于针对单变量时间序列信号实时检测离群值的方法和系统。该系统可以从数据源接收包括多个数据集的单变量时间序列信号。系统可以计算多个数据集中的一个数据集的标准偏差。随后,系统可以计算数据集的最佳样本块大小和临界样本大小。此外,系统可以确定数据集的最佳操作块大小。系统可以基于最佳操作块大小将多个数据集分割成块。系统可以通过对块执行离群值检测技术来检测离群值,从而确保改进的执行时间,同时最小化影响离群值检测方法的结果的准确性和准确性。

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