基于多级神经网络的桥梁结构参数优化设计

Optimal Design of Bridge Structural Parameters Based on Multi-level Neural Network

由于传统参数优化方法在对桥梁结构参数优化后无法实现对桥梁结构整体性能的有效提升,因此开展了基于多级神经网络的桥梁结构参数优化设计研究。通过构建桥梁结构有限元模型、基于多级神经网络确定桥梁结构参数优化目标、桥梁结构参数优化样本数据采集和桥梁结构参数多级神经网络参数优化求解,提出一种全新的参数优化方法。通过实验进一步证明,新的参数优化方法与传统参数优化方法相比,能够有效实现对桥梁结构综合性能的提升,为桥梁施工建设的增效减耗提供全新的优化思路。

Due to the traditional parameter optimization methods hard to realizing the effective improvement of the overall performance of the bridge structure after optimizing the bridge structure parameters,a research on the optimal design of bridge structure parameters based on multi-level neural networks is carried out.By establishing a finite element model of bridge structure,based on the multi-level neural network,the optimization goal of the bridge structure parameters is determined,the sample data for the optimization of the bridge structure parameters are collected,and the multi-level neural network parameters of the bridge structure are optimized and solved.A new parameter optimization method is proposed.The experiments have further proved that the new parameter optimization method can effectively improve the comprehensive performance of the bridge structure compared with the traditional parameter optimization method,which provides a new optimization idea for increasing the efficiency and reducing the consumption of bridge construction.