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Strain Monitoring Data Restoring of Large-span Steel Skybridge Based on BP Neural Network

ZHAO Xin1,JIA Jing2,ZHENG Yi-min1 (1.Architectural Design & Research Institute,Tongji University,Shanghai 200092,China;2.School of Civil Engineering,Tongji University,Shanghai 200092,China)  
In order to solve the problem of strain monitoring data absence in performance monitoring of large-span steel skybridge,the data restoring was carried out by using BP neural networks.Firstly,based on correlation analysis,five reference points which were most correlative with the data missing points were obtained,then the data of both reference points and data missing point in the stage were simulated and verified.All data were separated into two subsets: one for training the BP neural network model,and the other for validating the model.The missing data were restored by using the trained BP neural networks.Finally,the integrated strain monitoring data were gained,and the correlation coefficients of the data missing point and each reference point were calculated;comparing the correlation coefficients,the performance of data restoring was evaluated.The results show that this method can restore the missing strain monitoring data effectively.
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