Patents by Inventor Forooz Shahbazi Avarvand

Forooz Shahbazi Avarvand 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).

  • Anomaly detection using machine learning
    Patent number: 11851096
    Abstract: Examples of techniques for anomaly detection in a grade crossing prediction system are disclosed. Aspects include receiving a training data set comprising a plurality of labelled time series of signal values from a track circuit in a grade crossing predictor system, removing one or more non-unique values from each labelled time series of signal values in the plurality of labelled time series of signal values, extracting a plurality of features from the plurality of labelled time series of signal values, the plurality of features comprising: a number of signal values for each labeled time series of signal values in the plurality of labelled time series of signal values that are larger than a first threshold and a standard deviation for each labelled time series of signal values in the plurality of labelled time series of signal values, and training a machine learning algorithm utilizing the plurality of features.
    Type: Grant
    Filed: April 1, 2020
    Date of Patent: December 26, 2023
    Assignee: Siemens Mobility, Inc.
    Inventor: Forooz Shahbazi Avarvand
  • ANOMALY DETECTION USING MACHINE LEARNING
    Publication number: 20210309271
    Abstract: Examples of techniques for anomaly detection in a grade crossing prediction system are disclosed. Aspects include receiving a training data set comprising a plurality of labelled time series of signal values from a track circuit in a grade crossing predictor system, removing one or more non-unique values from each labelled time series of signal values in the plurality of labelled time series of signal values, extracting a plurality of features from the plurality of labelled time series of signal values, the plurality of features comprising: a number of signal values for each labeled time series of signal values in the plurality of labelled time series of signal values that are larger than a first threshold and a standard deviation for each labelled time series of signal values in the plurality of labelled time series of signal values, and training a machine learning algorithm utilizing the plurality of features.
    Type: Application
    Filed: April 1, 2020
    Publication date: October 7, 2021
    Inventor: Forooz Shahbazi Avarvand