Adaptive biases-incorporated latent factorization of tensors for predicting missing data in water quality monitoring networks

Adaptive biases-incorporated latent factorization of tensors for predicting missing data in water quality monitoring networks

Real-time monitoring of key water quality parameters is essential for the scientific management and effective maintenance of aquatic ecosystems. Water quality monitoring networks equipped with multiple low-cost electrochemical and optical sensors generate abundant spatiotemporal data for water autho...

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Bibliographic Details
Main Authors: Xuke Wu, Lan Wang, Miao Ge, Jing Jiang, Yu Cai, Bing Yang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Physics
Subjects:
multi-sensor data processing
water quality monitoring
machine learning
highdimensional and incomplete tensor
latent factorization of tensors
bias scheme
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2025.1587012/full
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https://www.frontiersin.org/articles/10.3389/fphy.2025.1587012/full

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