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1. 发明申请

US20100088074A1 MODELING OF THE RADIATION BELT MEGNETOSPHERE IN DECISIONAL TIMEFRAMES 有权
标题翻译：辐射带磁铁在决策时间的建模
公开(公告)号：US20100088074A1
公开(公告)日：2010-04-08
申请号：US12390611
申请日：2009-02-23
申请人： Josef KOLLER , Geoffrey D. REEVES , Reiner H. W. FRIEDEL
发明人： Josef KOLLER , Geoffrey D. REEVES , Reiner H. W. FRIEDEL
IPC分类号： G06F17/10 , G06F7/60 , G06F15/18 , G06N3/02
CPC分类号： G06N3/0445 , G01W1/10 , G06N3/0454
摘要： The calculation of L* in the magnetosphere can be calculated with essentially the same accuracy as with a physics based model at many times the speed by developing a surrogate trained to be a surrogate for the physics-based model. The trained model can then beneficially process input data falling within the training range of the surrogate model. The surrogate model can be a feedforward neural network and the physics-based model can be the TSK03 model.Operatively, the surrogate model can use parameters on which the physics-based model was based, spatial data for the location where L* is to be calculated. Surrogate models should be provided for each of a plurality of pitch angles. Accordingly, a surrogate model having a closed drift shell can be used from the plurality of models.The feedforward neural network can have a plurality of input-layer units, there being at least one input-layer unit for each physics-based model parameter; a plurality of hidden layer units; at least one output unit for the value of L*.
摘要翻译：磁层中L *的计算可以用基本上与物理基础的模型相同的精度来计算，通过开发经过训练成为基于物理学模型的替代品的替代品，速度的很多倍。训练后的模型可以有益地处理落在替代模型训练范围内的输入数据。代理模型可以是前馈神经网络，基于物理的模型可以是TSK03模型。代理模型可以使用基于物理的模型所依据的参数，计算L *的位置的空间数据。应为多个俯仰角中的每一个提供替代模型。因此，可以从多个模型中使用具有闭合漂移壳的替代模型。前馈神经网络可以具有多个输入层单元，每个基于物理的模型参数存在至少一个输入层单元; 多个隐层单元; 至少一个用于L *值的输出单元。

2. 发明授权

US08428916B2 Modeling of the radiation belt megnetosphere in decisional timeframes 有权
标题翻译：在决定时间范围内辐射带磁层的建模
公开(公告)号：US08428916B2
公开(公告)日：2013-04-23
申请号：US12390611
申请日：2009-02-23
申请人： Josef Koller , Geoffrey D. Reeves , Reiner H. W. Friedel
发明人： Josef Koller , Geoffrey D. Reeves , Reiner H. W. Friedel
IPC分类号： G06F7/60 , G06F17/10 , G06F15/18 , G06E1/00 , G06E3/00 , G06G7/00 , G06N3/02
CPC分类号： G06N3/0445 , G01W1/10 , G06N3/0454
摘要： Systems and methods for calculating L* in the magnetosphere with essentially the same accuracy as with a physics based model at many times the speed by developing a surrogate trained to be a surrogate for the physics-based model. The trained model can then beneficially process input data falling within the training range of the surrogate model. The surrogate model can be a feedforward neural network and the physics-based model can be the TSK03 model. Operatively, the surrogate model can use parameters on which the physics-based model was based, and/or spatial data for the location where L* is to be calculated. Surrogate models should be provided for each of a plurality of pitch angles. Accordingly, a surrogate model having a closed drift shell can be used from the plurality of models. The feedforward neural network can have a plurality of input-layer units, there being at least one input-layer unit for each physics-based model parameter, a plurality of hidden layer units and at least one output unit for the value of L*.
摘要翻译：用于通过开发经过训练成为基于物理学模型的替代品的替代品，在多个速度下以基于物理学的模型基本上相同的精度来计算磁层中的L *的系统和方法。训练后的模型可以有益地处理落在替代模型训练范围内的输入数据。代理模型可以是前馈神经网络，基于物理的模型可以是TSK03模型。代理模型可以使用基于物理的模型所基于的参数和/或用于计算L *的位置的空间数据。应为多个俯仰角中的每一个提供替代模型。因此，可以从多个模型中使用具有闭合漂移壳的替代模型。前馈神经网络可以具有多个输入层单元，存在用于每个基于物理的模型参数的至少一个输入层单元，多个隐含层单元和用于L *的值的至少一个输出单元。

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