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Method and Apparatus for Virtual Measurement for Calculating Predicted Value and Feature Importance Based on Feature Values of Time Series Data

机译:基于时间序列数据的特征值计算预测值和特征重要性的虚拟测量方法和装置

摘要

Disclosed are a virtual measurement method for calculating predicted values and feature importance based on feature values of time series data, and an apparatus therefor. A virtual measurement method according to an embodiment of the present invention includes: a time series data obtaining step of obtaining time series data including a time series type variable; a model learning processing step of extracting a feature value for the time series data, calculating a prediction value for learning based on the feature value, and generating a learning model; a virtual measurement processing step of calculating a virtual measurement result by applying new time series data to the learning model; and outputting a virtual measurement result of providing the virtual measurement result to an external device.
机译:公开了一种基于时间序列数据的特征值计算预测值和特征重要性的虚拟测量方法及其装置。根据本发明实施例的虚拟测量方法包括:时序数据获取步骤,获取包括时序类型变量的时序数据;模型学习处理步骤,提取所述时间序列数据的特征值,基于所述特征值计算用于学习的预测值,并生成学习模型;虚拟测量处理步骤,通过将新的时间序列数据应用于学习模型来计算虚拟测量结果;以及输出虚拟测量结果,以将虚拟测量结果提供给外部设备。

著录项

  • 公开/公告号KR20220028724A

    专利类型

  • 公开/公告日2022-03-08

    原文格式PDF

  • 申请/专利权人 (주)브릭;

    申请/专利号KR1020200110112

  • 申请日2020-08-31

  • 分类号H01L21/66;G05B13/04;G05B23/02;G06N3/04;G06N3/08;H01L21/67;

  • 国家 KR

  • 入库时间 2022-08-25 00:05:33

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