Multivariate time series imputation for energy data using neural networks
Multivariate time series with missing values are common in a wide range of applications, including energy data. Existing imputation methods often fail to focus on the temporal dynamics and the cross-dimensional correlation simultaneously. In this paper we propose a two-step method based on an attent...
Main Authors: | Christopher Bülte, Max Kleinebrahm, Hasan Ümitcan Yilmaz, Juan Gómez-Romero |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2023-07-01
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Series: | Energy and AI |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546823000113 |
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