Patents by Inventor Suresh Upparapalli

Suresh Upparapalli 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).

  • System and method for predicting response time of an enterprise system
    Patent number: 10467533
    Abstract: System and method for predicting enterprise system response time is disclosed. System pre-processes causal variables of historical output time series data to select subset of causal variables by applying regression techniques to obtain significant causal variables. Historical output time series data shows response time of enterprise system. System derives dummy variables from historical output time series data using threshold based method. Dummy variables are specific to peak detection and trough detection in historic output time series data. System trains predictive model using historical output time series data, significant causal variables, and dummy variables to generate trained predictive model and predictive model designed using machine learning technique selected based on forecast methodology used for forecasting input time series data.
    Type: Grant
    Filed: September 21, 2016
    Date of Patent: November 5, 2019
    Assignee: Tata Consultancy Services Limited
    Inventors: Kriti Kumar, Naveen Kumar Thokala, Ravikumar Karumanchi, Mariswamy Girish Chandra, Kalyan Prathap Kamakolanu Guru, Suresh Upparapalli, Madhusudhan Kamma Chavala Chowdary, Prasanna Madhavrao Kulkarni, Pareshkumar Bhawanishankar Sharda
  • SYSTEM AND METHOD FOR PREDICTING RESPONSE TIME OF AN ENTERPRISE SYSTEM
    Publication number: 20170185902
    Abstract: System and method for predicting enterprise system response time is disclosed. System pre-processes causal variables of historical output time series data to select subset of causal variables by applying regression techniques to obtain significant causal variables. Historical output time series data shows response time of enterprise system. System derives dummy variables from historical output time series data using threshold based method. Dummy variables are specific to peak detection and trough detection in historic output time series data. System trains predictive model using historical output time series data, significant causal variables, and dummy variables to generate trained predictive model and predictive model designed using machine learning technique selected based on forecast methodology used for forecasting input time series data.
    Type: Application
    Filed: September 21, 2016
    Publication date: June 29, 2017
    Applicant: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Kriti KUMAR, Naveen Kumar Thokala, Ravikumar Karumanchi, Mariswamy Girish Chandra, Kalyan Prathap Kamakolanu Guru, Suresh Upparapalli, Madhusudhan Kamma Chavala Chowdary, Prasanna Madhavrao Kulkarni, Pareshkumar Bhawanishankar Sharda