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SYSTEMS AND METHODS FOR SELECTING A FORECAST MODEL FOR ANALYZING TIME SERIES DATA

机译:选择用于分析时间序列数据的预测模型的系统和方法

摘要

Systems and methods for selecting a forecast model for analyzing time series data operate by identifying a characteristic of a set of time series data, then running tests on the time series data using multiple different forecast models. The forecast model that returns the fewest errors predicting future values of the time series data is selected for use for in analyzing time series data having the identified characteristic. This process is repeated for other sets of time series data having alternate characteristics to identify the forecast models that most accurately predict future values of time series data having those alternate characteristics. Thereafter, it is only necessary to identify the characteristics of a new set of time series data, and then use the forecast model that was selected for time series data having the identified characteristic in order to generate accurate predictions of future values for the new set of time series data.
机译:选择用于分析时间序列数据的预测模型的系统和方法通过识别一组时间序列数据的特征,然后使用多个不同的预测模型对时间序列数据进行测试来进行操作。选择返回最少的误差的预测模型来预测时间序列数据的未来值,以用于分析具有所识别特征的时间序列数据。对具有替代特征的其他时间序列数据集重复此过程,以识别最准确地预测具有那些替代特征的时间序列数据的未来值的预测模型。此后,仅需标识一组新的时间序列数据的特征,然后使用为具有所标识的特征的时间序列数据选择的预测模型,以便为该组新的序列的未来值生成准确的预测时间序列数据。

著录项

  • 公开/公告号US2019392252A1

    专利类型

  • 公开/公告日2019-12-26

    原文格式PDF

  • 申请/专利权人 NEW RELIC INC.;

    申请/专利号US201916451983

  • 申请日2019-06-25

  • 分类号G06K9/62;G06F17/18;

  • 国家 US

  • 入库时间 2022-08-21 11:22:15

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