Patents by Inventor Taisheng DU

Taisheng DU 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).

  • Farmland reference crop evapotranspiration prediction method considering uncertainty of meteorological factors
    Patent number: 12067079
    Abstract: A farmland reference crop evapotranspiration prediction method based on uncertainty of meteorological factors, includes: S1. acquiring a set number of groups of weather forecast data of a prediction region within a preset time period; S2. inputting each group of weather forecast data into a Bayesian probability forecast system to obtain corrected weather forecast data; and S3. inputting each group of the corrected weather forecast data into a trained RBF neural network, and predicting to obtain a farmland reference crop evapotranspiration. In the present invention, the Bayesian probability forecast system is configured to correct the weather forecast data and eliminate uncertainty of weather forecast data to obtain the accurate reference crop evapotranspiration forecasted by the RBF neural network using these data.
    Type: Grant
    Filed: January 8, 2021
    Date of Patent: August 20, 2024
    Assignee: CHINA INSTITUTE OF WATER RESOURCES AND HYDROPOWER RESEARCH
    Inventors: Baozhong Zhang, Zheng Wei, He Chen, Xin Han, Yinong Li, Taisheng Du, Zhigong Peng, Jiabing Cai, Congying Han, Yaqi Wang
  • FARMLAND REFERENCE CROP EVAPOTRANSPIRATION PREDICTION METHOD CONSIDERING UNCERTAINTY OF METEOROLOGICAL FACTORS
    Publication number: 20220100997
    Abstract: A farmland reference crop evapotranspiration prediction method based on uncertainty of meteorological factors, includes: S1. acquiring a set number of groups of weather forecast data of a prediction region within a preset time period; S2. inputting each group of weather forecast data into a Bayesian probability forecast system to obtain corrected weather forecast data; and S3. inputting each group of the corrected weather forecast data into a trained RBF neural network, and predicting to obtain a farmland reference crop evapotranspiration. In the present invention, the Bayesian probability forecast system is configured to correct the weather forecast data and eliminate uncertainty of weather forecast data to obtain the accurate reference crop evapotranspiration forecasted by the RBF neural network using these data.
    Type: Application
    Filed: January 8, 2021
    Publication date: March 31, 2022
    Applicant: China Institute of Water Resources and Hydropower Research
    Inventors: Baozhong ZHANG, Zheng WEI, He CHEN, Xin HAN, Yinong LI, Taisheng DU, Zhigong PENG, Jiabing CAI, Congying HAN, Yaqi WANG