Time Series Data and Recent Imputation Techniques for Missing Data: A Review-Reference-Cited by-同舟云学术

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Time Series Data and Recent Imputation Techniques for Missing Data: A Review

Published:2022-10-26 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Green Energy, Computing and Sustainable Technology (GECOST)
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Author:

Zainuddin Aznilinda¹,Hairuddin Muhammad Asraf¹,Yassin Ahmad Ihsan Mohd²,Latiff Zatul Iffah Abd¹,Azhar Aziemah³

Affiliation:

1. Universiti Teknologi MARA Johor Branch, Pasir Gudang Campus,Centre for Electrical Engineering Studies,Masai,Malaysia

2. Microwave Research Institute Universiti Teknologi MARA,Shah Alam,Malaysia

3. Malaysian Institute of Road Safety Research (MIROS),Vehicle Safety and Biomechanics Research Center,Kajang,Malaysia

Funder

Universiti Teknologi MARA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10009903/10009920/10010499.pdf?arnumber=10010499

Reference40 articles.

1. Imputation methods for addressing missing data in short-term monitoring of air pollutants

2. A large-scale sensor missing data imputation framework for dams using deep learning and transfer learning strategy

3. Handling missing data in near real-time environmental monitoring: A system and a review of selected methods

4. Partitioning around medoids clustering and random forest classification for GIS-informed imputation of fluoride concentration data

5. Towards missing electric power data imputation for energy management systems

Cited by 4 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. The impact of data imputation on air quality prediction problem;PLOS ONE;2024-09-12

2. Forecasting a Journal Impact Factor Under Missing Values Based on Machine Learning;IEEE Access;2024

3. Assessing the Multiple Imputation Approach for Univariate Time Series Data of Geomagnetic Disturbance Event in Solar Cycle 24;2023 IEEE Symposium on Computers & Informatics (ISCI);2023-10-14

4. Comparing Data-Driven and Expert-Driven Techniques for Enhanced Imputation in Marine Sensor Data;2023

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