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The estimation of spatially varying albedo and optical thickness in a radiating slab using artificial neural networks

机译:利用人工神经网络估计辐射板中空间反射率和光学厚度的变化。

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The inverse problem of estimating the single scattering abledo and optical thickness of a radiating slab from the knowledge of exit radiation intensities was accomplished by using an artificial neural network. Three training sets were developed which incorporated different amounts of training data. Simulated noisy measurement data was used to test the network. The network estimated the parameterized form of the spatially varying single scattering abledo and the optical thickness of the slab even when the amount of training data was limited to a few examples. The estimation of these parameters was more difficult, however, when the optical thickness was large.
机译:通过使用人工神经网络来完成根据出射辐射强度的知识估算辐射板的单个散射能力和光学厚度的反问题。开发了三个训练集,其中包含了不同数量的训练数据。模拟的噪声测量数据用于测试网络。即使训练数据量仅限于几个示例,网络也可以估计空间变化的单个散射能力的参数化形式和平板的光学厚度。但是,当光学厚度较大时,估计这些参数更加困难。

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