弹性波反源问题的神经网络方法  

Neural Network Method for the Inverse Source Problem of Elastic Wave

作　　者：柴媛媛 孟品超[1] 

机构地区：[1]长春理工大学数学与统计学院,吉林 长春

出　　处：《应用数学进展》2023年第2期690-697,共8页Advances in Applied Mathematics

摘　　要：针对弹性波点源的反演问题,构建基于全连接神经网络的点源位置和强度参数反演模型。以远场数据作为输入,以点源位置和强度参数作为输出,设计全连接神经网络,使用Adam优化算法更新网络的权重和偏置,进而反演点源的位置和强度。数值实验说明该方法对点源位置和强度反演问题是有效的。Aiming at the inverse point sources problem of elastic wave, the location and magnitude parame-ters inversion model is constructed based on fully connected neural network. Take far-field data as input, and take the location and magnitude parameters of point sources as output. We design a fully connected neural network and use Adam optimization algorithm to update the weight and bias of the model. Further, we can reconstruct the location and magnitude of the point sources. Numerical experiments show that this method is effective for inverse problem of location and magnitude of point sources.

关 键 词：反源问题 神经网络 点源 弹性波 远场数据 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]