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Causal relationship learning method, program, device, and anomaly analysis system

机译:因果关系学习方法,程序,设备和异常分析系统

摘要

The present invention provides a method, a program, and a device that can accurately learn a causal relationship in a deterministic system and a system that performs anomaly analysis by using the causal relationship. A causal relationship learning device according to one example embodiment of the present invention includes: a correlation determination unit that determines a correlation between measurement values measured by two sensors; and a low correlation causal relationship estimation unit that, when the correlation is lower than a predetermined reference, determines a causal relationship between the two sensors by estimating one of the measurement values which is a cause from the other of the measurement values which is a result.
机译:本发明提供了一种方法,程序和能够通过使用因果关系来准确地学习确定性系统中的因果关系的设备,以及通过使用因果关系执行异常分析的系统。根据本发明的一个示例实施例的因果关系学习设备包括:相关确定单元,其确定由两个传感器测量的测量值之间的相关性;和低相关因果关系估计单元,当相关性低于预定参考时,通过估计来自其他测量值的另一个的测量值之一来确定两个传感器之间的因果关系。

著录项

  • 公开/公告号US11073825B2

    专利类型

  • 公开/公告日2021-07-27

    原文格式PDF

  • 申请/专利权人 NEC CORPORATION;

    申请/专利号US201716608241

  • 发明设计人 MASASHI FUJITSUKA;

    申请日2017-04-27

  • 分类号G05B23/02;

  • 国家 US

  • 入库时间 2022-08-24 20:11:05

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