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Spatiotemporal water quality data reconstruction: A tensor factorization framework
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DOI：10.1016/j.ecoinf.2025.103283.png)
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Abstract
En 中文
• This study proposes seven-biased NTF model for improving water quality data imputation. • An ensemble method enhances accuracy across various missing scenarios. • Our proposed approach outperforms existing methods in both accuracy and computational efficiency. • Validation using AHFM data demonstrates effectiveness for practical water management.
Keywords:
Water quality
Missing data imputation
Nonnegative tensor factorization
Ensemble
Bias scheme
Lake Dianchi
Journal
IF:
7.3
Papers:
3.7K
Citations:
1.3W
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