反常扩散反问题中的神经网络和经典算法

2020 Science and Artificial Intelligence conference (S.A.I.ence) Pub Date : 2020-11-14 DOI:10.1109/S.A.I.ence50533.2020.9303217

V. A. Dedok, T. V. Bugueva

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引用次数: 0

摘要

本文提出了一种新的求解逆问题的数值方法。该方法可分为预测-校正方法，其中人工神经网络扮演预测器的角色，梯度法扮演校正器的角色。将该方法应用于反常扩散逆问题，并证明了其统计效率。

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Neural Networks and Classical Algorithms in Inverse Problems of Anomalous Diffusion

The paper develops a new numerical method for the solution of the inverse problems. This method can be classified as a predictor-corrector method, in which the artificial neural network plays the role of a predictor, and the gradient method plays the role of a corrector. We apply this method to inverse anomalous diffusion problem and show its statistical efficiency.

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2020 Science and Artificial Intelligence conference (S.A.I.ence)

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