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《Journal of Vibration and Shock》 2015-04
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Vibration response prediction of a powerhouse structure based on SSPSO-GRNN

XU Guo-bin;HAN Wen-wen;WANG Hai-jun;State Key Laboratory of Hydraulic Engineering Simulation and Safety,Tianjin University;Tianjin Pu Ze Engineering Consultion Co. ,Ltd.;  
Particle swarm optimization( PSO) algorithm is easy to fall into local extremum and premature convergence. To overcome defects of PSO,a new kind of PSO based on the survival of the fittest and step by step selection( SSPSO) was proposed here. Then,SSPSO was used to optimize smoothness parameter P of generalized regression neural network( GRNN). The advantages of the strong optimization ability of SSPSO and fewer parameters of GRNN were fully used. Then,the vibration response prediction model based on SSPSO-GRNN for a power-house structure was constructed based on the study data of a certain crest overflow hydropower station. The predicted results showed that the optimization capability of SSPSO is greatly improved compared with PSO; at the same time,the prediction accuracy,convergence performance and generalization ability of SSPSO-GRNN are better than those of other networks. The study results provided a new method for vibration response prediction of hydropower station houses to enhance their intelligent monitoring.
【Fund】: 国家自然科学基金创新研究群体科学基金项目(51321065)
【CateGory Index】: TV731;TV32
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