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《Sichuan Building Science》 2010-01
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Exploration of selection rules for inputs of neural network used on structural damage identification

ZHANG Yuzhi1,HE Wei2,LI Qiao1,SHAN Deshan1(1.School of Civil Engineering,Southwest Jiaotong University,Chengdu 610031,China;2.College of Sichuan Architectural Technology,Deyang 618000,China)  
When the diagnosis of damage location is taken as a problem of mode identification,neural network can be used as a pattern classifier.The identification effects will be affected by the number of the connotative layers and the nerve cells,the transfer function mode,the training samples,the training method and the performance of the inputs.Given the same conditions,the performance of the inputs is crucial to the performance of the neural network.To solve the problem of inputs sealection,three aspects:the function of the neural network,the separability of the inputs and the effect of noise,are taken into consideration.The selection rules of neural network inputs that have been put forward in this article is instructive to those who will use neural network to solve the problem of mode identification.
【Fund】: 西南交通大学青年教师科研起步资助项目(2007Q108);; 铁道部科技研究开发计划课题智能化桥梁结构研究(Z2006-048)
【CateGory Index】: TU317
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