摘要
自锚式悬索桥造型美观,且不需要庞大的锚碇。其将主缆锚固于加劲梁上,受力发生了极大的变化。因此,研究自锚式悬索桥的可靠性十分必要。采用BP神经网络法拟合可靠度计算的极限状态函数,引入粒子群算法优化神经网络法的初始权值,实现函数拟合的双优化,新算法则利用MATLAB编程实现。极限状态函数显化后,结合蒙特卡洛法计算自锚式悬索桥在正常使用极限状态下的可靠度。
The self-anchored suspension bridge has the advantages of beautiful appearance, and does not need huge anchor. The main cable is anchored in the stiffening girder, its stress changed. Therefore, study on the reliability of self-anchored suspension bridge is very necessary. Using BP neural network method to fit the reliability calculation of the limit state function, bringing in the initial weight of particle swarm optimization neural network method, realize the dual optimization function fitting, a new algorithm using MATLAB programming. To manifest the limit state function, calculate the self-anchored suspension bridge in reliability under serviceability limit states with Monte Carlo method.
出处
《城市建筑》
2013年第10期264-264,275,共2页
Urbanism and Architecture
