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《Journal of Lanzhou University of Technology》 2006-02
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Prediction of structural dynamic response based on RBF neural network

DU Yong-feng,GUO Jian-hong(College of Civil Engineering,Lanzhou Univ.of Tech.,Lanzhou 730050,China)  
Constitutive features of radial basis function(RBF),such as fast neural network learning,strong dynamic simulation ability,good input/output mapping function,and global optimal approaching,were introduced.Taking into consideration of the feature that fast prediction of structural dynamic response is useful for overcoming the time-lag effect in structural vibration control,and aiming at the existing problems in BP network,the RBF network was employed to predict the displacement and acceleration of the construction.The RBF network was also used to conduct comparison investigation.Simulation result showed that there were fast training and high accuracy with RBF neural network,so that it could provide more accurate optimal performance indexes for timely active control of structural response of the buildings and good guarantee for implementing on-line real-time control of structural response.
【Fund】: 甘肃省自然科学基金(ZS021-A25-015-G)
【CateGory Index】: TU311.3
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