Abstract With the increasing frequency and intensity of earthquakes, the idea of seismic design continues to develop, and it must be ensured that the structure not only has sufficient strength, but also has certain ductility. However, there is currently no suitable method for effective evaluation of seismic performance. In order to find a method with high accuracy, this paper uses BP neural network algorithm and RBF neural network algorithm to analyze and control the collision response of urban bridge adjacent beam and pier beam under strong earthquake. In this paper, the prediction of concrete carbonation depth and steel corrosion is carried out. The comparison of simulation results shows that the prediction effect of RBF network is better than that of BP network. In this paper, based on the skeleton curve calculated by bending shear failure test column, bending curve, shear deformation and longitudinal reinforcement drawing deformation are considered. The results are in good agreement with the hysteresis curve and can be used to calculate the reinforced concrete column under axial load and horizontal load. As the IM index gradually increases, the damage and failure probability of the bridge structure IDA show a relatively rapid upward trend. Then, when IM approaches 3.5 g, the failure probability of the bridge reaching the corresponding side shift ratio of 1.75% is more than 95%.

中文翻译：

---

BP神经网络与RBF神经网络在墩柱抗震性能评价中的对比分析

摘要 随着地震频率和烈度的增加，抗震设计思想不断发展，必须保证结构既要有足够的强度，又要有一定的延性。然而，目前还没有合适的方法来进行有效的抗震性能评价。为了找到一种高精度的方法，本文采用BP神经网络算法和RBF神经网络算法对强震作用下城市桥梁相邻梁和墩梁碰撞响应进行分析和控制。本文对混凝土碳化深度和钢筋锈蚀进行了预测。仿真结果对比表明，RBF网络的预测效果优于BP网络。在本文中，以弯曲剪切破坏试验柱计算的骨架曲线为基础，考虑弯曲曲线、剪切变形和纵向钢筋拉拔变形。计算结果与滞后曲线吻合较好，可用于计算钢筋混凝土柱在轴向荷载和水平荷载作用下。随着IM指数逐渐升高，桥梁结构IDA的损坏和失效概率呈现较快的上升趋势。那么，当 IM 接近 3.5 g 时，桥梁达到相应侧移比 1.75% 的失效概率超过 95%。计算结果与滞后曲线吻合较好，可用于计算钢筋混凝土柱在轴向荷载和水平荷载作用下。随着IM指数逐渐升高，桥梁结构IDA的损坏和失效概率呈现较快的上升趋势。那么，当 IM 接近 3.5 g 时，桥梁达到相应侧移比 1.75% 的失效概率超过 95%。计算结果与滞后曲线吻合较好，可用于计算钢筋混凝土柱在轴向荷载和水平荷载作用下。随着IM指数逐渐升高，桥梁结构IDA的损坏和失效概率呈现较快的上升趋势。那么，当 IM 接近 3.5 g 时，桥梁达到相应侧移比 1.75% 的失效概率超过 95%。