Patents by Inventor Bhupendra Suresh Bendale

Bhupendra Suresh Bendale 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).

  • COMPUTERIZED ENGINES AND GRAPHICAL USER INTERFACES FOR CUSTOMIZING AND VALIDATING FORECASTING MODELS
    Publication number: 20230297809
    Abstract: Some examples can involve a system that can receive a first user selection of time series data and a second user selection of a type of forecasting model to apply to the time series data. The system can then obtain a first set of candidate values and a second set of candidate values for a first parameter and a second parameter, respectively, of the selected type of forecasting model. The candidate values may be determined based on statistical information derived from the time series data. The system can then provide the first set of candidate values and the second set of candidate values to the user, receive user selections of a first parameter value and a second parameter value, and determine whether a conflict exists between the first parameter value and the second parameter value. If so, the system can generate an output indicating that the conflict exists.
    Type: Application
    Filed: February 27, 2023
    Publication date: September 21, 2023
    Inventors: Iman Vasheghani Farahani, Ron Travis Hodgin, Sujatha Pothireddy, Kaushal Lalitkumar Chauhan, Bhupendra Suresh Bendale, Harshad Dinesh Bapat, Kritika Misra
  • Computerized engines and graphical user interfaces for customizing and validating forecasting models
    Patent number: 11748597
    Abstract: Some examples can involve a system that can receive a first user selection of time series data and a second user selection of a type of forecasting model to apply to the time series data. The system can then obtain a first set of candidate values and a second set of candidate values for a first parameter and a second parameter, respectively, of the selected type of forecasting model. The candidate values may be determined based on statistical information derived from the time series data. The system can then provide the first set of candidate values and the second set of candidate values to the user, receive user selections of a first parameter value and a second parameter value, and determine whether a conflict exists between the first parameter value and the second parameter value. If so, the system can generate an output indicating that the conflict exists.
    Type: Grant
    Filed: February 27, 2023
    Date of Patent: September 5, 2023
    Assignee: SAS Institute, Inc.
    Inventors: Iman Vasheghani Farahani, Ron Travis Hodgin, Sujatha Pothireddy, Kaushal Lalitkumar Chauhan, Bhupendra Suresh Bendale, Harshad Dinesh Bapat, Kritika Misra
  • Computer implemented systems for automatic hierarchy for large scale time series data sets
    Patent number: 10540377
    Abstract: A hierarchical structure (e.g., a hierarchy) for use in hierarchical analysis (e.g., hierarchical forecasting) of timestamped data can be automatically generated. This automated approach to determining a hierarchical structure involves identifying attributes of the timestamped data, clustering the timestamped data to select attributes for the hierarchy, ordering the attributes to achieve a recommended hierarchical order, and optionally modifying the hierarchical order based on user input. Through the approach disclosed herein, a hierarchy can be generated that is designed to perform well under hierarchical models. This recommended hierarchy for use in hierarchical analysis may be agnostic to any planned hierarchy provided by or used by a user to otherwise interpret the timestamped data.
    Type: Grant
    Filed: April 9, 2019
    Date of Patent: January 21, 2020
    Assignee: SAS INSTITUTE INC.
    Inventors: Yue Li, Neha Bindumadhav Kulkarni, Yung-Hsin Chien, Sagar Arun Mainkar, Bhupendra Suresh Bendale
  • COMPUTER IMPLEMENTED SYSTEMS FOR AUTOMATIC HIERARCHY FOR LARGE SCALE TIME SERIES DATA SETS
    Publication number: 20190317952
    Abstract: A hierarchical structure (e.g., a hierarchy) for use in hierarchical analysis (e.g., hierarchical forecasting) of timestamped data can be automatically generated. This automated approach to determining a hierarchical structure involves identifying attributes of the timestamped data, clustering the timestamped data to select attributes for the hierarchy, ordering the attributes to achieve a recommended hierarchical order, and optionally modifying the hierarchical order based on user input. Through the approach disclosed herein, a hierarchy can be generated that is designed to perform well under hierarchical models. This recommended hierarchy for use in hierarchical analysis may be agnostic to any planned hierarchy provided by or used by a user to otherwise interpret the timestamped data.
    Type: Application
    Filed: April 9, 2019
    Publication date: October 17, 2019
    Applicant: SAS Institute Inc.
    Inventors: Yue Li, Neha Bindumadhav Kulkarni, Yung-Hsin Chien, Sagar Arun Mainkar, Bhupendra Suresh Bendale