Missing Value Imputation Based on Gaussian Mixture Model for the Internet of Things
Joint Authors
Hu, Liang
Wang, Feng
Zhao, Kuo
Yan, Xiaobo
Xiong, Weiqing
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-02
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
This paper addresses missing value imputation for the Internet of Things (IoT).
Nowadays, the IoT has been used widely and commonly by a variety of domains, such as transportation and logistics domain and healthcare domain.
However, missing values are very common in the IoT for a variety of reasons, which results in the fact that the experimental data are incomplete.
As a result of this, some work, which is related to the data of the IoT, can’t be carried out normally.
And it leads to the reduction in the accuracy and reliability of the data analysis results.
This paper, for the characteristics of the data itself and the features of missing data in IoT, divides the missing data into three types and defines three corresponding missing value imputation problems.
Then, we propose three new models to solve the corresponding problems, and they are model of missing value imputation based on context and linear mean (MCL), model of missing value imputation based on binary search (MBS), and model of missing value imputation based on Gaussian mixture model (MGI).
Experimental results showed that the three models can improve the accuracy, reliability, and stability of missing value imputation greatly and effectively.
American Psychological Association (APA)
Yan, Xiaobo& Xiong, Weiqing& Hu, Liang& Wang, Feng& Zhao, Kuo. 2015. Missing Value Imputation Based on Gaussian Mixture Model for the Internet of Things. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1074121
Modern Language Association (MLA)
Yan, Xiaobo…[et al.]. Missing Value Imputation Based on Gaussian Mixture Model for the Internet of Things. Mathematical Problems in Engineering No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1074121
American Medical Association (AMA)
Yan, Xiaobo& Xiong, Weiqing& Hu, Liang& Wang, Feng& Zhao, Kuo. Missing Value Imputation Based on Gaussian Mixture Model for the Internet of Things. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1074121
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074121