Patents by Inventor Deyan LIU

Deyan LIU 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, apparatus and device for optimizing process parameter, and storage medium
    Patent number: 12596857
    Abstract: The present application pertains to the field of data processing technology, specifically relates to a method, apparatus and device for optimizing a process parameter and a storage medium, which includes: using a first weight parameter of a pre-trained support vector regression model for a manufacturing equipment as an iterative initial value, and calculating a second weight parameter of a support vector regression model using an online proximal gradient algorithm based on training data; obtaining an optimized support vector regression model by updating the first weight parameter of the pre-trained support vector regression model to the second weight parameter; inputting a first process parameter of the manufacturing equipment into the optimized support vector regression model to obtain a first detection parameter output by the optimized support vector regression model; and calculating, according to the first process parameter and the first detection parameter, a target process parameter for the manufacturing
    Type: Grant
    Filed: April 10, 2025
    Date of Patent: April 7, 2026
    Assignees: COSMO INSTITUTE OF INDUSTRIAL INTELLIGENCE (QINGDAO) CO., LTD., COSMOPlat IoT Technology Co., Ltd.
    Inventors: Lucheng Chen, Deyan Liu, Chao Wang, Chenggang Qin, Lin Wang, Qingze Tian, Xiang Li
  • METHOD, APPARATUS AND DEVICE FOR OPTIMIZING PROCESS PARAMETER, AND STORAGE MEDIUM
    Publication number: 20250335667
    Abstract: The present application pertains to the field of data processing technology, specifically relates to a method, apparatus and device for optimizing a process parameter and a storage medium, which includes: using a first weight parameter of a pre-trained support vector regression model for a manufacturing equipment as an iterative initial value, and calculating a second weight parameter of a support vector regression model using an online proximal gradient algorithm based on training data; obtaining an optimized support vector regression model by updating the first weight parameter of the pre-trained support vector regression model to the second weight parameter; inputting a first process parameter of the manufacturing equipment into the optimized support vector regression model to obtain a first detection parameter output by the optimized support vector regression model; and calculating, according to the first process parameter and the first detection parameter, a target process parameter for the manufacturing
    Type: Application
    Filed: April 10, 2025
    Publication date: October 30, 2025
    Inventors: Lucheng CHEN, Deyan LIU, Chao WANG, Chenggang QIN, Lin WANG, Qingze TIAN, Xiang LI