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SYSTEM AND METHOD FOR DETECTING AND PREDICTING ANOMALIES BASED ON ANALYSIS OF TIME-SERIES DATA

机译:基于时间序列数据分析的异常检测与预测系统及方法

摘要

Provided are a system and method for detecting and predicting anomalies based on analysis of time-series data. According to an embodiment of the present disclosure, an abnormality detecting and predicting system includes a database configured to store past case data related to a state of a monitored object; a data collector configured to collect time-series status information of the monitored object; an abnormality detector configured to compare the status information with an abnormality detecting reference in a preset detecting interval and detect an occurrence of an abnormality of the monitored object; a similar case selector configured to select a similar case having a highest degree of similarity to the status information among the past case data when the occurrence of an abnormality is detected by the abnormality detector; and a predictor configured to predict proliferation or diminishing of a detected abnormality using the similar case and an abnormality proliferation predicting reference.
机译:提供了一种基于时间序列数据的分析来检测和预测异常的系统和方法。根据本公开的实施例,异常检测和预测系统包括:数据库,被配置为存储与被监视对象的状态有关的过去病例数据;以及数据收集器,用于收集被监控对象的时间序列状态信息;异常检测器,用于在预定的检测间隔内将所述状态信息与所述异常检测参考进行比较,并检测出所述被监控对象的异常情况;相似案例选择器,被配置为当由异常检测器检测到异常发生时,在过去案例数据中选择与状态信息具有最高相似度的相似案例;预测器,被配置为使用相似的情况和异常增殖预测基准来预测检测到的异常的增殖或减少。

著录项

  • 公开/公告号US2016103724A1

    专利类型

  • 公开/公告日2016-04-14

    原文格式PDF

  • 申请/专利权人 SAMSUNG SDS CO. LTD.;

    申请/专利号US201414582746

  • 发明设计人 SUNGIL KIM;HYUNTAEK OH;SUNDEUK KIM;

    申请日2014-12-24

  • 分类号G06F11/07;

  • 国家 US

  • 入库时间 2022-08-21 14:38:32

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