CommentsThis whitepaper reflects the author's own perspectives on the NWQ software ecosystem and does not represent an official position of PNNL, UW, or the U.S. Department of Energy
AgriPINN: A Process-Informed Neural Network for Interpretable and Scalable Crop Biomass Prediction Under Water Stress
AgriPINN:一种过程指导的神经网络,用于在水分胁迫下可解释且可扩展的作物生物量预测
Yue Shi, Liangxiu Han, Xin Zhang, Tam Sobeih, Thomas Gaiser, Nguyen Huu Thuy, Dominik Behrend, Amit Kumar Srivastava, Krishnagopal Halder, Frank Ewert
机构
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Department of Computing, and Mathematics, Faculty of Science and Engineering(计算与数学系,科学与工程学院)
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Manchester Metropolitan University(曼彻斯特 Metropolitan 大学)
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Leibniz Centre for Agricultural Landscape Research (ZALF)(莱比锡农业景观研究中心(ZALF))
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Institute of Crop Science and Resource Conservation (INRES)(作物科学与资源保护研究所)