摘要
结合5个在低周期反复荷载作用下的钢骨高强混凝土柱/钢筋高强混凝土梁框架节点的试验研究,描绘了节点的骨架曲线·利用神经网络的原理,通过建立神经网络的输入层、隐含层、输出层,确定输入单元、输出单元和隐含层节点数,从而建立了神经网络的模型,并根据已有的一些数据,对网络进行训练,使其具有分析和判断的功能,从而对钢骨高强混凝土框架节点的骨架曲线进行了预测·结果表明,这种方法是可行的·
Based on the testing results of 5 joints at a steel reinforced high-strength concrete column/reinforced high-strength concrete girder frame, some P～Δ curves have been generated under the action of low-frequency cyclic load. Based on the principle of BP neural network, a model is developed by way of setting up the input, implicit and output layers with input and output cells and number of nodes or joints of implicit level all determined. Then, the network is trained up according to some given data to enable it to serve the functions of analysis and judgement so as to forecast the P～Δ curves generated from the joints of a steel reinforced high-strength concrete frame. The results showed the feasibility of the method proposed.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第1期92-94,共3页
Journal of Northeastern University(Natural Science)
基金
辽宁省自然科学基金资助项目(2001101012)
国家建设部科技攻关项目(2002-2-11)
关键词
钢骨高强混凝土柱
钢筋高强混凝土梁
框架节点
骨架曲线
BP网络
steel reinforced high-strength concrete column
reinforced high-strength concrete girder
frame joint
P-Δ curves
BP network
