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篇名
A Method for Detecting Abnormal Data of Network Nodes Based on Convolutional Neural Network
並列篇名
A Method for Detecting Abnormal Data of Network Nodes Based on Convolutional Neural Network
作者 Xianhao Shen (Xianhao Shen)Changhong  Zhu (Changhong  Zhu)Yihao Zang (Yihao Zang)Shaohua Niu (Shaohua Niu)
英文摘要

Abnormal data detection is an important step to ensure the accuracy and reliability of node data in wireless sensor networks. In this paper, a data classification method based on convolutional neural network is proposed to solve the problem of data anomaly detection in wireless sensor networks. First, Normal data and abnormal data generated after injection fault are normalized and mapped to gray image as input data of the convolutional neural network. Then, based on the classical convolution neural network, three new convolutional neural network models are designed by designing the parameters of the convolutional layer and the fully connected layer. This model solves the problem that the performance of traditional detection algorithm is easily affected by relevant threshold through self-learning data characteristics of convolution layer. The experimental results show that this method has better detection performance and higher reliability.

 

起訖頁 049-058
關鍵詞 data anomaly detectionconvolutional neural networkinjection faultnormal
刊名 電腦學刊  
期數 202206 (33:3期)
該期刊-上一篇 Prediction of Academic Formulaic Language based on Multi-feature Fusion
該期刊-下一篇 Stall Warning Algorithm of Axial Compressor Based on SSA-DBN
 

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