Crop production response climate change relation model construction method
By constructing a model of the relationship between crop production and climate change response and using Mean-Shift and GMM algorithms, we have solved the problem of insufficient systematic research on the response of crop production to climate change, provided scientific basis and decision-making support, and improved the adaptability and efficiency of agricultural production.
CN120597083AActive Publication Date: 2025-09-05HUAZHI RICE BIO TECH CO LTD
Patent Information
- Application Number
- CN202510632177.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-16
- Publication Date
- 2025-09-05
- Estimated Expiration
- 2045-05-16
Smart Images
Figure CN120597083A_ABST
Abstract
The invention provides a method for constructing a crop production response climate change relation model, and relates to the crossing field of agricultural meteorology and data analysis, and the method comprises the steps: carrying out the mean shift clustering calculation of a crop phenotype data set, and obtaining a preliminary clustering result; performing Gaussian mixture clustering calculation on the preliminary clustering result to obtain a central point of the original data; performing curve fitting calculation of four functions on the data center point under each meteorological factor to obtain a fitting result; and calculating a mean square error value of each function according to a fitting result, selecting a corresponding fitting function according to a minimum mean square error, and finally constructing a meteorological factor and crop phenotype relationship model. According to the method, the advantages of Mean-Shift and GMM algorithms are fused, a quantitative relation model is constructed to reveal the dynamic influence of climate change on crop production, the problems that a traditional clustering algorithm is sensitive to singular values and the selection subjectivity of a fitting function is high are effectively solved, and a scientific basis is provided for agricultural climate adaptability management.
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Citation Information
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