基于BP神经网络的建筑结构隔震初步设计系统
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摘要
基于BP人工神经网络,以建筑结构的抗震设防类别、设防烈度、场地类别、地震分组、高宽比、长宽比、刚度,质量和面积为主要影响因子,以隔震后结构的最大层剪力比和支座最大位移作为输出结果,建立一个隔震初步设计系统。经25个训练样本对该网络进行训练后,利用15个测试样本对网络进行了测试。通过测试结果与实际设计结果的对比,网络的平均准确率达到96%,说明基于BP神经网络的隔震初步设计系统对隔震结构的减震效果分析具有高效性和准确性。
Based on BP neural network,as the seismic fortification type,fortification intensity,site type,seismic design group,height-width ratio,aspect ratio,stiffness,mass and of structure to main impact factor,as the maximum shear force ratio and the largest displacement of isolation bearing to output data,a base isolation structural initial design system is set up.After trained network by 25 training samples,it is used to test 15 test samples.It is show that accuracy is 96% by comparing test with actual design results,which indicates that the analysis results of base isolation structure by base isolation structural initial design system based on BP neural network are more effective and accurate.
Based on BP neural network,as the seismic fortification type,fortification intensity,site type,seismic design group,height-width ratio,aspect ratio,stiffness,mass and of structure to main impact factor,as the maximum shear force ratio and the largest displacement of isolation bearing to output data,a base isolation structural initial design system is set up.After trained network by 25 training samples,it is used to test 15 test samples.It is show that accuracy is 96% by comparing test with actual design results,which indicates that the analysis results of base isolation structure by base isolation structural initial design system based on BP neural network are more effective and accurate.
引文
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[9]赵艳林,杨军平,黄剑飞,吕海波.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):491～496Zhao Yan-ling,Yang Jun-ping,Huang Jian-fei,Lv Hai-bo.Seismic Damage Prediction for Single-storyReinforced Concrete Industrial Building Based On BackPropagation Neural Network[J].Journal of GuilinUniversity of Technology,2006,26(4):491～496(inChinese)
[10]郑浩,王全风.BP神经网络在高层结构选型中的应用[J].华侨大学学报,2003,24(1):48～55Zheng Hao,Wang Quan-feng.Application of BP NeuralNet to the Choice of Structural System for a High-riseBuilding[J].Journal of Huaqiao University,2003,24(1):48～55(in Chinese)
[2]党育,杜永峰,李慧.基础隔震结构设计及施工指南[M].北京:中国水利水电出版社,2007Dang Yu,Du Yong-feng,Li Hui.Base IsolationStructure Design and Constrction Guide[M].Beijing:Water Conservancy and Hydropower Publishing House ofChina,2007(in Chinese)
[3]魏东.非线性系统神经网络参数预测及控制[M].北京:机械工业出版社,2008Wei Dong.Nonlinear System Neural Network ParameterPrediction and Control[M].Beijing:MachineryIndustry Publishing House,2008(in Chinese)
[4]杜永峰,李慧.高效神经网络训练及其在桁架损伤识别中的应用[J].华中科技大学学报,2008,25(4):51～53Du Yong-feng,Li Hui.High Efficiency Training Methodfor Artificial Neural Network and Its Application toDamage Identification of Truss[J].Journal of HUST,2008,25(4):51～53(in Chinese)
[5]李慧,王红丽,杜永峰,张东兵.基于改进BP算法的刚框架连接损伤识别方法[J].甘肃科学学报,2007,19(2):114～117Li Hui,Wang Hong-li,Du Yong-feng,Zhang Dong-bing.Identification of Connection Damage of Steel FrameBased onImproved BP Algorithm[J].Journal of GansuSciences,2007,19(2):114～117(in Chinese)
[6]韩立群.人工神经网络理论、设计及应用[M].北京:化学工业出版社,2002Han Li-qun.Artifical Neural Network Theory,Designand Application[M].Beijing:Chemical IndustryPublishing House,2002(in Chinese)
[7]李慧,王红丽,杜永峰.钢框架连接损伤的两种改进BP算法的比较[J].工程抗震与加固改造,2006,28(6):39～42Li Hui,Wang Hong-li,Du Yong-feng.ComparativeAnalysis of Two Kinds of Improved BP Algorithm Usedfor Structural Damage Identification[J].EarthquakeResistant Engineering and Retrofitting,2006,28(6):39～42(in Chinese)
[8]许东,吴铮.基于MATLAB 6.X的系统分析与设计——神经网络[M].西安:西安电子科技大学出版社,2002Xu Dong,Wu Zheng.System Analysis and Design BaseOn MATLAB 6.X[M].Xian:Xidian UniversityPublishing House,2002(in Chinese)
[9]赵艳林,杨军平,黄剑飞,吕海波.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):491～496Zhao Yan-ling,Yang Jun-ping,Huang Jian-fei,Lv Hai-bo.Seismic Damage Prediction for Single-storyReinforced Concrete Industrial Building Based On BackPropagation Neural Network[J].Journal of GuilinUniversity of Technology,2006,26(4):491～496(inChinese)
[10]郑浩,王全风.BP神经网络在高层结构选型中的应用[J].华侨大学学报,2003,24(1):48～55Zheng Hao,Wang Quan-feng.Application of BP NeuralNet to the Choice of Structural System for a High-riseBuilding[J].Journal of Huaqiao University,2003,24(1):48～55(in Chinese)
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