Missing value interpolation algorithm for long-term temperature observation data based on data augmentation multiple interpolation method
Temperature data exhibit obvious heterogeneity both in time and space. Long-term missing data can disrupt the continuous spatiotemporal heterogeneity and periodic characteristics of the original data, making it difficult to calculate the initial estimated value of the data. This leads to the randomn...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025022832 |
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