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Detection, characterization, and prediction of real-time events occurring approximately periodically

机译:检测,表征和预测大致周期性发生的实时事件

摘要

Systems and methods for detection, characterization, and prediction of real-time events having approximate periodicity include detection of events from raw data that are approximately periodic. The detection includes analyzing raw data to determine approximately periodic chains of events. The raw data can be related to network management systems, financial monitoring systems, medical monitoring, seismic activity monitoring, or any system that performs some management or monitoring of an underlying system or network having time lasting events. The detected approximately periodic events could be characterized and presented in natural language as well as used for prediction of future events via supervised machine learning.
机译:用于检测,表征和预测具有近似周期性的实时事件的系统和方法包括从大约周期性的原始数据检测事件。 该检测包括分析原始数据以确定事件的大约周期性链。 原始数据可以与网络管理系统,财务监测系统,医学监测,地震活动监控或任何执行一些管理或监控具有时间持久事件的网络的任何系统。 检测到的大约周期性事件可以以自然语言表征和呈现,并通过监督机器学习来预测未来事件。

著录项

  • 公开/公告号US2021248138A1

    专利类型

  • 公开/公告日2021-08-12

    原文格式PDF

  • 申请/专利权人 EXFO SOLUTIONS SAS;

    申请/专利号US202117169735

  • 发明设计人 FABRICE PELLOIN;

    申请日2021-02-08

  • 分类号G06F16/2458;G06F16/242;G06F16/2457;G06N20;G06F16/248;

  • 国家 US

  • 入库时间 2022-08-24 20:34:02

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