基于神经网络的动脉壁最大剪应力预测方法

M. Blagojevic, Milos D. Radovic, M. Radovic, N. Filipovic
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引用次数: 1

摘要

本文介绍了人工神经网络在动脉瘤壁面最大剪应力预测中的应用。为了训练神经网络,采用了反向传播算法。网络中的输入数据为动脉瘤模型的几何参数。所得结果表明,神经网络在动脉某些参数预测问题上有成功应用的可能性。未来的工作涉及到创建一个基于web的应用程序,允许用户显示结果。
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Neural network based approach for predicting maximal wall shear stress in the artery
This paper describes the use of artificial neural networks in predicting value and position maximal wall shear stress in aneurysm. For the purpose of neural network training, back propagation algorithm was used. Input data in the network are geometric parameters of aneurysm model. Obtained results indicate the possibility of a successful application of neural networks in the problems of predicting certain parameters of arteries. Future work relates to the creation of a web-based application that allows users to display the results.
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