首页|基于循环神经网络的结构动力学求解方法探究

基于循环神经网络的结构动力学求解方法探究

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传统的结构动力学方程求解方法通常基于微分方程求解、数值方法和模拟技术,但存在计算复杂度高和收敛速度慢的问题.为寻求新的解决途径,文中提出了一种基于循环神经网络(RNN)的新方法,用于模拟和解析结构的动态反应.通过将RNN应用于简单的结构动力学案例,成功实现了对结构动力学方程的预测和模拟.结果表明模型平均相对误差均在10-4,该模型准确捕捉了结构的动态特征,展现了出色的性能.
APPLICATION OF STRUCTURAL DYNAMICS SOLUTION METHODS BASED ON RECURRENT NEURAL NETWORK
Traditional methods for solving structural dynamic equations are usually based on differential equations,numerical methods,and simulation techniques,suffering from high computational complexity and slow convergence.In order to seek a new solution path,we propose a new method based on recurrent neural networks(RNN)for model-ing and resolving the dynamic response of structures.By applying RNN to a simple case of structural dynamics,we successfully realize the prediction and simulation of structural dynamic equations.The results show that the average relative errors of the model are all in the range of 10-4,and the model accurately captures the dynamic characteristics of the structure and demonstrates excellent performance.

structural dynamicsrecurrent neural networkdifferential equation

赵铎阳、曾森

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青岛理工大学土木工程学院,山东青岛 266525

结构动力学 循环神经网络 微分方程

2024

低温建筑技术
黑龙江省寒地建筑科学研究院

低温建筑技术

影响因子:0.237
ISSN:1001-6864
年,卷(期):2024.46(5)