A Lightweight-Window-Portion-Based Multiple Imputation for Extreme Missing Gaps in IoT Systems-Reference-Cited by-同舟云学术

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A Lightweight-Window-Portion-Based Multiple Imputation for Extreme Missing Gaps in IoT Systems

Published:2024-02-01 Issue:3 Volume:11 Page:3676-3689
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Adhikari Deepak¹^ORCID,Jiang Wei¹^ORCID,Zhan Jinyu¹^ORCID,Assefa Maregu¹^ORCID,Khorshidi Hadi A.²^ORCID,Aickelin Uwe²^ORCID,Rawat Danda B.³^ORCID

Affiliation:

1. Department of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China

2. School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia

3. Department of Electrical Engineering and Computer Science, Howard University, Washington, DC, USA

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10413935/10250789.pdf?arnumber=10250789

Reference41 articles.

1. A Comprehensive Survey on Imputation of Missing Data in Internet of Things

2. The Internet of Things

3. Missing value imputation on multidimensional time series

4. Yoga Meets Intelligent Internet of Things: Recent Challenges and Future Directions

5. Missing Data Imputation With Bayesian Maximum Entropy for Internet of Things Applications

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Recent advances in anomaly detection in Internet of Things: Status, challenges, and perspectives;Computer Science Review;2024-11

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