单层钢筋混凝土柱工业厂房震害非线性预测模型及应用
|
摘要
将RBF人工神经网络理论应用于等高单层钢筋混凝土柱工业厂房的震害预测。在分析震害特点的基础上,将震害影响因子分为精确性和规律性两大类,提出以地震反应指标、天窗类型、支撑情况、建筑材料作为主要的影响指标。然后将震害等级作为输出结果,构造了震害预测的非线性预测模型。通过对52个实际震害实例的检验,网络的准确率高,可见该模型是有效可靠的。
The RBF artificial neural network is applied to predict seismic damage of single-story reinforced concrete industrial building.Based on the analysis of characteristics of seismic damage,it is found that earthquake response index,type of sky light,bracing system and building material are the ma in factors affecting seismic damage.The four factors can be classified into two types:precise factors and regular factors.The corresponding spans of factors are suggested and applied to engineering examples.Thus the RBF artificial neural network is developed,with factors affecting seismic dam age as input and seismic damage grade as output.It was verified by 52 engineering examples.It is concluded that the RBF artificial neural network developed in this paper is applicable to predictseismic damage of single-story reinforced concrete industrial building.
The RBF artificial neural network is applied to predict seismic damage of single-story reinforced concrete industrial building.Based on the analysis of characteristics of seismic damage,it is found that earthquake response index,type of sky light,bracing system and building material are the ma in factors affecting seismic damage.The four factors can be classified into two types:precise factors and regular factors.The corresponding spans of factors are suggested and applied to engineering examples.Thus the RBF artificial neural network is developed,with factors affecting seismic dam age as input and seismic damage grade as output.It was verified by 52 engineering examples.It is concluded that the RBF artificial neural network developed in this paper is applicable to predictseismic damage of single-story reinforced concrete industrial building.
引文
[1]王晓明,朱伯龙.基于二次模糊修正的钢筋混凝土单层工业厂房震害预测综合评判模式[J].建筑结构学报,1994,15(1):32-38.
[2]李桂青,李正农.建筑物和构筑物震害的灰色预测方法[J].湖北工学院学报,1992,7(3/4):7-12.
[3]赵艳林,杨军平,黄剑飞,等.基于BP神经网络的单层钢筋混凝土柱工业厂房震害预测[J].桂林工学院学报,2006,26(4):491-496.
[4]吴育才,黄宗明,王金海.单层厂房震例及其应用[M].济南:山东科学技术出版社,1991:152-225.
[5]尹之潜,李树桢,杨淑文,等.震害与地震损失的估计方法[J].地震工程与工程震动,1990,10(1):99-107.
[6]王光远,徐祥文,周锡元,等.单层厂房自振特性及其在地震反应计算中的应用[C]//地震工程研究报告集(第一集).北京:科学出版社,1962:51-75.
[7]李红,彭涛.基于BP、RBF神经网络混凝土抗压强度预测[J].武汉理工大学学报,2009,31(8):33-36.
[2]李桂青,李正农.建筑物和构筑物震害的灰色预测方法[J].湖北工学院学报,1992,7(3/4):7-12.
[3]赵艳林,杨军平,黄剑飞,等.基于BP神经网络的单层钢筋混凝土柱工业厂房震害预测[J].桂林工学院学报,2006,26(4):491-496.
[4]吴育才,黄宗明,王金海.单层厂房震例及其应用[M].济南:山东科学技术出版社,1991:152-225.
[5]尹之潜,李树桢,杨淑文,等.震害与地震损失的估计方法[J].地震工程与工程震动,1990,10(1):99-107.
[6]王光远,徐祥文,周锡元,等.单层厂房自振特性及其在地震反应计算中的应用[C]//地震工程研究报告集(第一集).北京:科学出版社,1962:51-75.
[7]李红,彭涛.基于BP、RBF神经网络混凝土抗压强度预测[J].武汉理工大学学报,2009,31(8):33-36.
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心