Patents by Inventor Muhammad Haris MALIK

Muhammad Haris MALIK 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).

  • Method and apparatus for characterizing composite materials using an artificial neural network
    Patent number: 9274036
    Abstract: This invention relates to a method and apparatus for characterizing composite materials, and in particular, to utilizing an artificial neural network for predicting an impact resistance of a composite material. A method for predicting an impact resistance of a composite material in accordance with the present invention includes the steps of designing an artificial neural network including a plurality of neurons, training the artificial neural network to predict the impact resistance by adjusting an output of the plurality of neurons according to sample data and known results of the sample data, inputting data of the composite material into the artificial neural network, and utilizing the artificial neural network to predict the impact resistance of the composite material.
    Type: Grant
    Filed: December 13, 2013
    Date of Patent: March 1, 2016
    Assignee: King Fahd University of Petroleum and Minerals
    Inventors: Muhammad Haris Malik, Abdul Fazal Muhammad Arif
  • METHOD AND APPARATUS FOR CHARACTERIZING COMPOSITE MATERIALS USING AN ARTIFICIAL NEURAL NETWORK
    Publication number: 20150170022
    Abstract: This invention relates to a method and apparatus for characterizing composite materials, and in particular, to utilizing an artificial neural network for predicting an impact resistance of a composite material. A method for predicting an impact resistance of a composite material in accordance with the present invention includes the steps of designing an artificial neural network including a plurality of neurons, training the artificial neural network to predict the impact resistance by adjusting an output of the plurality of neurons according to sample data and known results of the sample data, inputting data of the composite material into the artificial neural network, and utilizing the artificial neural network to predict the impact resistance of the composite material.
    Type: Application
    Filed: December 13, 2013
    Publication date: June 18, 2015
    Applicant: King Fahd University of Petroleum and Minerals
    Inventors: Muhammad Haris MALIK, Abdul Fazal Muhammad ARIF