Patents by Inventor Himanshu Panwar

Himanshu Panwar 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).

  • Building time series based prediction / forecast model for a telecommunication network
    Patent number: 11900282
    Abstract: The present disclosure relates to system(s) and method(s) for building an ARIMA based Time Series prediction/forecast model for Key Performance Indicators (KPIs) and Performance Management (PM) counters in a telecommunication network. The system receives historical data, for a predefined period, associated with a prediction/forecast model. The system further pre-processes the historical data in order to evaluate statistical characteristics of stationarity of the historical data. Based on the evaluation, the system stationarizes the data first by backfilling anomalies and missing data and then applying techniques associated with differencing, moving averages and auto-correlation. The system further builds the Time Series based prediction/forecast model using the data using ACF and PACF correlation functions.
    Type: Grant
    Filed: January 21, 2020
    Date of Patent: February 13, 2024
    Assignee: HCL TECHNOLOGIES LIMITED
    Inventors: Rahul Soundrarajan, Himanshu Panwar
  • BUILDING TIME SERIES BASED PREDICTION / FORECAST MODEL FOR A TELECOMMUNICATION NETWORK
    Publication number: 20210224699
    Abstract: The present disclosure relates to system(s) and method(s) for building an ARIMA based Time Series prediction/forecast model for Key Performance Indicators (KPIs) and Performance Management (PM) counters in a telecommunication network. The system receives historical data, for a predefined period, associated with a prediction/forecast model. The system further pre-processes the historical data in order to evaluate statistical characteristics of stationarity of the historical data. Based on the evaluation, the system stationarizes the data first by backfilling anomalies and missing data and then applying techniques associated with differencing, moving averages and auto-correlation. The system further builds the Time Series based prediction/forecast model using the data using ACF and PACF correlation functions.
    Type: Application
    Filed: January 21, 2020
    Publication date: July 22, 2021
    Inventors: Rahul Soundrarajan, Himanshu Panwar