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<div><p>Accurate prediction of crop phenological stage is essential for evaluating management strategies and assessing crop responses to environmental changes. In this work, we modified Non-dominated Sorting Genetic Algorithm with the core algorithm of PEST (MNSGA-II) and compared it to...

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Main Author:	Yonghui Zhang (279832) (author)
Other Authors:	Yujie Zhang (399434) (author), Haiyan Jiang (39944) (author), Liang Tang (48583) (author), Xiaojun Liu (58952) (author), Weixing Cao (575808) (author), Yan Zhu (112437) (author)
Published:	2025
Subjects:	Genetics Biotechnology Ecology Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified soybean phenology using soybean phenological model mean absolute error little difference among evaluating management strategies crop phenological stage crop model parameter crop model according case study using assessing crop responses simulated data based independent experimental data relatively ideal algorithm div >< p source data observed data suitable algorithm source datasets rmse ), results provide modified non mae ), exactly simulate environmental changes differential evolution core algorithm certain advantage actual requirements accurate prediction
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