公开(公告)号：US20170061297A1

公开(公告)日：2017-03-02

申请号：US15233610

申请日：2016-08-10

Applicant: SAS Institute Inc.

Inventor： KALYAN JOSHI ,  NITZI ROEHL ,  YUNG-HSIN (ALEX) CHIEN

IPC: G06N5/04

CPC classification number: G06N5/04

Abstract: Data sets for a three-stage predictor can be automatically determined. For example, multiple time series can be filtered to identify a subset of time series that have time durations that exceed a preset time duration. Whether a time series of the subset of time series includes a time period with inactivity can be determined. Whether the time series exhibits a repetitive characteristic can be determined based on whether the time series has a pattern that repeats over a predetermined time period. Whether the time series includes a magnitude spike with a value above a preset magnitude can be determined. If the time series (i) lacks the time period with inactivity, (ii) exhibits the repetitive characteristic, and (iii) has the magnitude spike with the value above the preset magnitude threshold, the time series can be included in a data set for use with the three-stage predictor.

Abstract translation: 可以自动确定三级预测器的数据集。 例如，可以过滤多个时间序列以识别具有超过预设持续时间的持续时间的时间序列子集。 可以确定时间序列子集的时间序列是否包含具有不活动的时间段。 可以基于时间序列是否具有在预定时间段内重复的图案来确定时间序列是否具有重复特性。 可以确定时间序列是否包括具有高于预设幅度的值的幅度尖峰。 如果时间序列（i）缺乏不活动的时间段，（ii）表现出重复特性，（iii）具有高于预设幅度阈值的值的幅度峰值，时间序列可以包括在数据集中 与三级预测器一起使用。

公开(公告)号：US20180039897A1

公开(公告)日：2018-02-08

申请号：US15788238

申请日：2017-10-19

Applicant: SAS Institute Inc.

Inventor： KALYAN JOSHI ,  NITZI ROEHL ,  YUNG-HSIN (ALEX) CHIEN

IPC: G06N5/04

CPC classification number: G06N5/04

Abstract: Data sets for a three-stage predictor can be automatically determined. For example, multiple time series can be filtered to identify a subset of time series that have time durations that exceed a preset time duration. Whether a time series of the subset of time series includes a time period with inactivity can be determined. Whether the time series exhibits a repetitive characteristic can be determined based on whether the time series has a pattern that repeats over a predetermined time period. Whether the time series includes a magnitude spike with a value above a preset magnitude can be determined. If the time series (i) lacks the time period with inactivity, (ii) exhibits the repetitive characteristic, and (iii) has the magnitude spike with the value above the preset magnitude threshold, the time series can be included in a data set for use with the three-stage predictor.

公开(公告)号：US20170061296A1

公开(公告)日：2017-03-02

申请号：US15233400

申请日：2016-08-10

Applicant: SAS Institute Inc.

Inventor： KALYAN JOSHI ,  NITZI ROEHL ,  YUNG-HSIN (ALEX) CHIEN

IPC: G06N5/04

CPC classification number: G06N5/04

Abstract: Information related to a time series can be predicted. For example, a repetitive characteristic of the time series can be determined by analyzing the time series for a pattern that repeats over a predetermined time period. An adjusted time series can be generated by removing the repetitive characteristic from the time series. An effect of a moving event on the adjusted time series can be determined. The moving event can occur on different dates for two or more consecutive years. A residual time series can be generated by removing the effect of the moving event from the adjusted time series. A base forecast that is independent of the repetitive characteristic and the effect of the moving event can be generated using the residual time series. A predictive forecast can be generated by including the repetitive characteristic and the effect of the moving event into the base forecast.

Abstract translation: 可以预测与时间序列有关的信息。 例如，可以通过分析在预定时间段内重复的图案的时间序列来确定时间序列的重复特性。 可以通过从时间序列中去除重复特性来生成经调整的时间序列。 可以确定移动事件对经调整的时间序列的影响。 移动事件可以在两个或多个连续的年份的不同日期发生。 可以通过从调整的时间序列中消除移动事件的影响来生成剩余时间序列。 可以使用剩余时间序列来生成独立于重复特性和移动事件的影响的基础预测。 可以通过将重复性特征和移动事件的影响包括在基础预测中来产生预测性预测。