An Outlier Cleaning Algorithm Based on Deep Learning
2022-02
发表期刊电子与信息学报 (IF:0.5[JCR-2023],0.4[5-Year])
ISSN1009-5896
卷号44期号:2页码:507-513
发表状态已发表
DOI10.11999/JEIT201097
摘要

The use of appropriate abnormal data cleaning algorithms in the Internet of Things (IoT) can greatly improve data quality. Statistical methods or clustering methods are utilized to clean anomalies in Spatio-temporal data. However, these methods require additional prior knowledge, which will incur additional computational overhead for the sink node. In this paper, in line with the low-rank sparse matrix decomposition model, a fast anomaly cleaning algorithm based on a deep neural network is proposed to solve the Spatio-temporal data cleaning problem in IoT. Both the Spatio-temporal correlation of sensing data and the abnormal values' sparsity are considered in an optimization problem. The Iterative Shrinkage-Thresholding Algorithm (ISTA) is used to solve it. Then the ISTA is unfolded into a fixed-length deep neural network. The real-world dataset's experimental results show that the proposed method can automatically update the thresholds faster and more accurately than the traditional ISTA. © 2022, Science Press. All right reserved.

关键词Big data Cleaning Internet of things Iterative methods Shrinkage Abnormal data Clustering methods Data cleaning Data quality Internet of thing Iterative shrinkage-thresholding algorithm Iterative shrinkagethresholding algorithms Outlier cleaning Spatio-temporal data Unfoldings
收录类别EI ; ESCI ; 北大核心
语种中文
出版者Science Press
EI入藏号20220911731990
EI主题词Deep neural networks
EI分类号461.4 Ergonomics and Human Factors Engineering ; 722.3 Data Communication, Equipment and Techniques ; 723 Computer Software, Data Handling and Applications ; 723.2 Data Processing and Image Processing ; 802.3 Chemical Operations ; 921.6 Numerical Methods ; 951 Materials Science
原始文献类型Journal article (JA)
文献类型期刊论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/159567
专题信息科学与技术学院_硕士生
信息科学与技术学院_特聘教授组_钱骅组
通讯作者Qian, Hua
作者单位
1.Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai; 201210, China;
2.School of Information Science and Technology, ShanghaiTech University, Shanghai; 201210, China;
3.University of Chinese Academy of Sciences, Beijing; 100049, China;
4.School of Microelectronics, University of Chinese Academy of Sciences, Beijing; 100049, China;
5.Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai; 200050, China
第一作者单位信息科学与技术学院
通讯作者单位信息科学与技术学院
推荐引用方式
GB/T 7714
Kuang, Junqian,Zhao, Chang,Yang, Liu,et al. An Outlier Cleaning Algorithm Based on Deep Learning[J]. 电子与信息学报,2022,44(2):507-513.
APA Kuang, Junqian,Zhao, Chang,Yang, Liu,Wang, Haifeng,&Qian, Hua.(2022).An Outlier Cleaning Algorithm Based on Deep Learning.电子与信息学报,44(2),507-513.
MLA Kuang, Junqian,et al."An Outlier Cleaning Algorithm Based on Deep Learning".电子与信息学报 44.2(2022):507-513.
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