基于人工神经网络的钢筋混凝土异型节点抗剪承载力预测  

Prediction on anti-shear capacity of RC abnormal joints based on artificial neural networks

作　　者：白建方[1] 白国良[1] 张淑云[2] 

机构地区：[1]西安建筑科技大学土木工程学院,陕西西安710055 [2]西安科技大学建工系,陕西西安710054

出　　处：《西安建筑科技大学学报（自然科学版）》2004年第2期171-175,共5页Journal of Xi'an University of Architecture & Technology(Natural Science Edition)

基　　金：国家电力工业总公司重点资助项目(60-Y2002-03-T03);陕西省教育厅专项基金项目(03JK142)

摘　　要：研究了利用神经网络技术分析钢筋混凝土框架异型节点抗震性能的可行性.从前馈神经网络原理分析出发,利用神经网络方法研究了低周反复荷载作用下的钢筋混凝土框架异型节点抗剪承载力与各主要影响因素之间复杂的非线性关系,并建立了承载力的BP神经网络预测模型.通过与试验结果相对比,新方法获得了令人满意的结果.分析结果表明神经网络计算在钢筋混凝土框架异型节点的抗震行为和力学特性研究领域是一种切实可行且极具发展潜力的新方法.The paper investigates the feasibility of using neural networks to analyze the seismic behavior of abnormal joints of reinforced concrete frame. According to the mechanism of feed forward Neural Network, Neural Networks technology is applied to built the complex non-linear relationship between the anti-shear capacities of the reinforced concrete abnormal joints under low reversed cyclic loading and the main factors. Back Propagation (BP)Neural Networks model is built to predict the strength of the reinforced concrete abnormal joints. According to the test data, satisfactory results are achieved. Therefore, it is proven that the neurocomputing is a practical and promising tool for the analysis on seismic behavior and mechanical properties of abnormal joints of reinforced concrete frame.

关 键 词：人工神经网络 钢筋混凝土异型节点 抗剪承载力 

分 类 号：TU375.4[建筑科学—结构工程]