MACHINE LEARNING-BASED PREDICTION OF DISSOLVED OXYGEN LEVELS IN RIVER ECOSYSTEMS
Keywords:
Dissolved oxygen, River ecosystem, Machine learning, Environmental Monitoring, Predictive Modeling.Abstract
Dissolved oxygen (DO) is a key indicator of river water quality and plays a critical role in sustaining
aquatic ecosystems. Adequate DO levels are essential for the respiration and survival of aquatic
organisms, making it vital to monitor and predict
References
Hutchins MG, Qu Y, Charlton MB. Successful modelling of river dissolved oxygen dynamics requires knowledge of stream channel environments. J Hydrol. 2021;603:126991.
Xu C, Luo P, Wu P, Song C, Chen X. Detection of periodicity, aperiodicity, and corresponding driving factors of river dissolved oxygen based on high-frequency measurements. J Hydrol. 2022;609:127711.
Downloads
Published
2025-04-15
How to Cite
Dr. P. Babu, U. Satya Narayana, P. Uma Sai Krishna, V. Bharathi. (2025). MACHINE LEARNING-BASED PREDICTION OF DISSOLVED OXYGEN LEVELS IN RIVER ECOSYSTEMS. Journal of Computational Analysis and Applications (JoCAAA), 34(4), 1311–1319. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3129
Issue
Section
Articles
