【摘要】 本文将遗传算法与神经网络相结合,从而建立了一种高效的、实用的桥梁震害预测方法。根据遗传算法具有局部寻优的特点,为避免BP神经网络陷入局部极小值,本文将二者结合起来形成GA-BP混合算法,以GA优化神经网络的初始权值和阈值,对网络进行训练。在大量收集梁式桥震害资料的基础上,将此算法引入桥梁的震害预测中,并与传统的单独BP神经网络相比较,结果表明该方法能够有效、准确地对桥梁结构进行震害预测。更多还原

【Abstract】 The paper presents an effective method for predicting the seismic damage to bridges.To avoid the BP algorithm′s shortcoming of trapping in a local optimum and to take advantage of the genetic algorithm′s globe optimal searching,a new kind of hybrid algorithm was formed based on GA and BP in this paper.First,the initialized weights and threshold of BP neural network was optimized with GA,and then train the network with GA-BP.After collecting a great deal of information of girder-style bridges,the hybrid algorithm was introduced into the earthquake damage prediction,then compare with the single BP neural network.The results show that GA-BP algorithm is an effective and accurate method for seismic damage prediction of bridges.更多还原