Invention Grant
- Patent Title: Demand classification based pipeline system for time-series data forecasting
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Application No.: US16726616Application Date: 2019-12-24
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Publication No.: US10685283B2Publication Date: 2020-06-16
- Inventor: Yue Li , Michele Angelo Trovero , Phillip Mark Helmkamp , Jerzy Michal Brzezicki , Macklin Carter Frazier , Timothy Patrick Haley , Randy Thomas Solomonson , Sangmin Kim , Steven Christopher Mills , Yung-Hsin Chien , Ron Travis Hodgin , Jingrui Xie
- Applicant: SAS Institute Inc.
- Applicant Address: US NC Cary
- Assignee: SAS INSTITUTE INC.
- Current Assignee: SAS INSTITUTE INC.
- Current Assignee Address: US NC Cary
- Agency: Kilpatrick Townsend & Stockton LLP
- Priority: com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@7e958c03
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F16/2458 ; G06F16/28 ; G06N3/04 ; G06F16/242 ; G06F16/248 ; G06F16/26 ; H04L12/24

Abstract:
A pipeline system for time-series data forecasting using a distributed computing environment is disclosed herein. In one example, a pipeline for forecasting time series is generated. The pipeline represents a sequence of operations for processing the time series to produce modeling results such as forecasts of the time series. The pipeline includes a segmentation operation for categorizing the time series into multiple demand classes based on demand characteristics of the time series. The pipeline also includes multiple sub-pipelines corresponding to the multiple demand classes. Each of the sub-pipelines applies a model strategy to the time series in the corresponding demand class. The model strategy is selected from multiple candidate model strategies based on predetermined relationships between the demand classes and the candidate model strategies. The pipeline is executed to determine the modeling results for the time series.
Public/Granted literature
- US20200143246A1 DEMAND CLASSIFICATION BASED PIPELINE SYSTEM FOR TIME-SERIES DATA FORECASTING Public/Granted day:2020-05-07
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