基于粗糙集—RBF神经网络的单层RC厂房震害预测
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摘要
RBF神经网络具有较好的仿真预测功能,粗糙集理论可以通过属性约简、重要度排序等对样本数据进行有效筛选。将粗糙集与RBF神经网络有机结合,建立单层RC厂房的震害预测模型。结合实际震例进行仿真训练,得到的单层RC厂房震害预测值与实际值基本吻合。表明该模型可对单层工业厂房进行较为有效的震害预测,且对震害预防也具有一定的指导意义。
Radial Basis Function neural network has good function of simulation prediction.Rough set theory can filter samples effectively through attribution reduction and attribute importance ranking.Rough set theory and artificial neural network are integrated into a model of seismic damage prediction for single-story reinforced concrete industrial building.The prediction results agree with actual seismic damage of single-story reinforced concrete industrial building.It shows that this model can be well used in the field of seismic damage prediction for single-story reinforced concrete industrial building and has guiding significance in the field of seismic damage prevention.
Radial Basis Function neural network has good function of simulation prediction.Rough set theory can filter samples effectively through attribution reduction and attribute importance ranking.Rough set theory and artificial neural network are integrated into a model of seismic damage prediction for single-story reinforced concrete industrial building.The prediction results agree with actual seismic damage of single-story reinforced concrete industrial building.It shows that this model can be well used in the field of seismic damage prediction for single-story reinforced concrete industrial building and has guiding significance in the field of seismic damage prevention.
引文
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[2]周丽萍,温娟娟,等.基于神经网络的交通事故仿真预测方法[J].计算机仿真,2009,26(5):299～302Zhou Li-ping,Wen Juan-juan,et al.Simulated Prediction Of Traffic Accident Based on Radial Basis Function Neural Network[J].Computer Simulation,2009,26(5):299～302(in Chinese)
[3]赵艳林,杨军平,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):491～496Zhao Yan-lin,Yang Jun-ping,et al.Seismic Damage Prediction For Single-story Reinforced Concrete Industrial Building Based on Back Propagation Neural Network[J].Journal of Guilin University of Technology,2006,26(4):491～496(in Chinese)
[4]王光远,徐祥文,等.单层厂房自振特性及其在地震反应计算中的应用[A].地震工程研究报告集(第一集)[C],北京:科学出版社,1962:51～75Wang Guang-yuan,Xu Xiang-wen,et al.Since the Vibration Characteristics of Single-storey Factory Building and Its Application in the Calculation of Seismic Response[C].Beijing:Science Press,1962:51～75(in Chinese)
[5]吴育才,黄宗明.单层厂房震例及其应用[M].济南:山东科学技术出版社,1991:152～225Wu Yu-cai,Huang Zong-ming.Cases And Applicationof Single-storey Factory Building Earthquake[M].Jinan:Shandong Science And Technology Press,1991:152～225(in Chinese)
[6]周丽萍,宋早雪,等.基于BP神经网络电子评标方法的研究和应用[J].南京工业大学学报,2007,29(4):85～89Zhou Li-ping,Song Zao-xue,et al.Evaluation Method Based On BP Neural Network In Tendering[J].Journal of Nanjing University of Technology,2007,29(4):85～89(in Chinese)
[7]郭剑虹,刘建新,等.RBF网络的结构动力响应预测[J].工程抗震与加固改造,2007,29(5):49～52Guo Jian-hong,Liu Jian-xin,et al.Prediction of Structural Dynamic Response with RBF Neural Network[J].Earthquake Resistant Engineering and Retrofitting,2007,29(5):49～52(in Chinese)
[8]PAWLAK Z.Rough Sets and Intelligent Data Analysis[J].Journal of Information Sciences,2002(147):1～12
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