Patents by Inventor Yingfei BAI

Yingfei BAI 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, system and equipment for vegetation restoration or rehabilitation based on machine learning
    Patent number: 11694005
    Abstract: A method for vegetation restoration or rehabilitation of simulating a natural ecosystem based on machine learning (ML) includes: acquiring historical growth environment data of a vegetation community; extracting a site condition feature and a growth condition feature of each vegetation species; restoring and rehabilitating a vegetation community structure selection model; and selecting, based on the vegetation community structure selection model, an optimal vegetation species according to current growth environment data of the vegetation community, and restoring and rehabilitating a vegetation community simulating a natural ecosystem. The method comprehensively considers various factors affecting vegetation restoration based on the site condition and the growth condition.
    Type: Grant
    Filed: October 18, 2022
    Date of Patent: July 4, 2023
    Assignee: China Institute of Water Resources and Hydropower Research
    Inventors: Guangquan Liu, Wanli Shi, Liu Liu, Chunyu Qi, Yingfei Bai, Puhang Li, Qiang Zhang, Yonggui Chen, Heng Fu
  • METHOD, SYSTEM AND EQUIPMENT FOR VEGETATION RESTORATION OR REHABILITATION OF SIMULATING NATURAL ECOSYSTEM BASED ON MACHINE LEARNING
    Publication number: 20230123790
    Abstract: A method for vegetation restoration or rehabilitation of simulating a natural ecosystem based on machine learning (ML) includes: acquiring historical growth environment data of a vegetation community; extracting a site condition feature and a growth condition feature of each vegetation species; restoring and rehabilitating a vegetation community structure selection model; and selecting, based on the vegetation community structure selection model, an optimal vegetation species according to current growth environment data of the vegetation community, and restoring and rehabilitating a vegetation community simulating a natural ecosystem. The method comprehensively considers various factors affecting vegetation restoration based on the site condition and the growth condition.
    Type: Application
    Filed: October 18, 2022
    Publication date: April 20, 2023
    Applicant: China Institute of Water Resources and Hydropower Research
    Inventors: Guangquan LIU, Wanli SHI, Liu LIU, Chunyu QI, Yingfei BAI, Puhang LI, Qiang ZHANG, Yonggui CHEN, Heng FU