Dissolved Oxygen Modeling by a Bayesian-Optimized Explainable Artificial Intelligence Approach

Dissolved Oxygen Modeling by a Bayesian-Optimized Explainable Artificial Intelligence Approach

Dissolved oxygen (DO) is a vital water quality index influencing biological processes in aquatic environments. Accurate modeling of DO levels is crucial for maintaining ecosystem health and managing freshwater resources. To this end, the present study contributes a Bayesian-optimized explainable mac...

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Bibliographic Details
Main Authors: Qiulin Li, Jinchao He, Dewei Mu, Hao Liu, Shicheng Li
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
dissolved oxygen
machine learning
interpretability
Bayesian optimization
Online Access:https://www.mdpi.com/2076-3417/15/3/1471
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https://www.mdpi.com/2076-3417/15/3/1471

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