Comparison of Missing Data Imputation Methods in Time Series Forecasting-Reference-Cited by-同舟云学术

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Comparison of Missing Data Imputation Methods in Time Series Forecasting

Published:2022 Issue:1 Volume:70 Page:767-779
ISSN:1546-2226
Container-title:Computers, Materials & Continua
language:en
Short-container-title:

Author:

Ahn Hyun,Sun Kyunghee,Pio Kim Kwanghoon

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanics of Materials,Modeling and Simulation,Biomaterials

Link

https://www.techscience.com/cmc/v70n1/44403/pdf

Cited by 32 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

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4. Improving Time-Series Forecasting Performance Using Imputation Techniques in Deep Learning;2024 International Conference on Smart Computing, IoT and Machine Learning (SIML);2024-06-06

5. The Comparison of Missing Value Imputation for Price Index Forecasting Based on ARIMA Model;2024 21st International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON);2024-05-27

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