Yield prediction model of rice and wheat crops based on ecological distance algorithm

文献类型： 外文期刊

第一作者： Tian, Li

作者： Tian, Li;Wang, Chun;Li, Hailiang;Sun, Haitian

作者机构：

关键词： Ecological distance algorithm; Total sensitivity index; Pearson correlation coefficient; Rice and wheat crops; Yield prediction model

期刊名称：ENVIRONMENTAL TECHNOLOGY & INNOVATION （ 影响因子：5.263； 五年影响因子：5.116 ）

ISSN： 2352-1864

年卷期： 2020 年 20 卷

页码：

收录情况： SCI

摘要： Aiming at the problem that the original yield prediction model of rice and wheat crops has low prediction accuracy in use, yield prediction model of rice and wheat crops based on the ecological distance algorithm. According to the design process, weather parameters, soil parameters, and behavioral parameters were obtained as crop yield impact parameters. Using this parameter in combination with the Pearson correlation coefficient and the total sensitivity index, the data assimilation technique was used to determine the crop yield predictor. The ecological distance algorithm was combined with crop yield predictors to construct a yield prediction model of rice and wheat crops. Compared with the original yield prediction model, the output forecast result of this model is closer to the sample result. In summary, the yield prediction model of rice and wheat based on Ecological distance algorithm has higher prediction accuracy. (C) 2020 Elsevier B.V. All rights reserved.

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