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《Systems Engineering and Electronics》 2018-02
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Monitoring data repairing method based on deep denoising auto-encoder network

CHEN Haiyan;DU Jinghan;ZHANG Weining;College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics;Collaborative Innovation Center of Novel Software Technology and Industrialization;  
In view of the frequent failure of monitoring points and data anomalies,a monitoring data repairing method based on deep denoising auto-encoder(DDAE)network is proposed.Firstly,the denoising auto-encoder(DAE)is used as the basic structural unit to construct the DDAE network.Then,the deep correlation of the data is extracted from the DDAE network,and the support vector regression(SVR)model is constructed to predict the monitoring data to be repaired.Experiments conducted on the airport noise data set demonstrate that the deep correlation can reconstruct the noise monitoring data very well.Compared with the traditional data repairing methods,the proposed data repairing method has better robustness and higher precision.
【Fund】: 国家自然科学基金(61501229);; 中央高校基本科研业务费专项资金(NS2015091 NJ20160013)资助课题
【CateGory Index】: TN929.5;TP391.44
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