Patents by Inventor STEVEN CHRISTOPHER MILLS

STEVEN CHRISTOPHER MILLS has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Demand classification based pipeline system for time-series data forecasting
    Patent number: 10685283
    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.
    Type: Grant
    Filed: December 24, 2019
    Date of Patent: June 16, 2020
    Assignee: SAS INSTITUTE INC.
    Inventors: 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
  • DEMAND CLASSIFICATION BASED PIPELINE SYSTEM FOR TIME-SERIES DATA FORECASTING
    Publication number: 20200143246
    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.
    Type: Application
    Filed: December 24, 2019
    Publication date: May 7, 2020
    Applicant: SAS Institute Inc.
    Inventors: 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