phygnn:物理学指导的神经网络(phygnn)

上传者: 42097450 | 上传时间: 2023-03-06 11:07:31 | 文件大小: 7.89MB | 文件类型: ZIP
菌素 phygnn (fi-geon | ˈfi-jən)名词。 物理学指导的神经网络 一只稀有的神话鸟 物理学指导的神经网络的这种实现通过通用的损失项增强了传统的神经网络损失功能,该损失项可用于指导神经网络学习物理或理论约束。 phygnn使科学软件开发人员和数据科学家能够轻松地将机器学习模型集成到物理和工程应用程序中。当将纯数据驱动的机器学习模型应用于科学应用时,例如当机器学习模型产生物理上不一致的结果或难以推广到样本外场景时,此框架应有助于缓解一些经常遇到的挑战。 有关phygnn类框架的详细信息,请参见 例如,使用phygnn架构进行回归,分类甚至GAN应用,请参见 在国家可再生能源实验室(NREL),我们使用phygnn框架来补充传统的基于卫星的云属性预测模型。当传统的机械模型失效时,我们使用phygnn预测云的光学特性,并使用基于张量的完整辐射传递模型作为物理损耗函数,将预测

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