CN CN122472929A
本发明涉及智慧农业技术领域，具体涉及一种植物水分利用策略解析方法、系统及存储介质，采集环境时序、植物生理时序及高光谱图像多模态数据并进行特征级融合；构建基于注意力机制的第一预测模型，输出蒸腾速率预测值并提取环境因子贡献权重；构建基于生态一致性约束的第二预测模型，预测土壤体积含水量和基质势以补全环境数据缺失；通过交替迭代的协同耦合训练，使两个模型相互促进，显著增强数据缺失条件下蒸腾预测的鲁棒性；基于蒸腾速率时间序列聚类划分水分利用策略类型；利用注意力权重量化各环境因子对不同策略类型的影响程度。本发明可缓解湿地环境中关键数据缺失导致的精度缺陷，增强了模型的泛化能力和生态一致性。
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