Utilizing machine learning models to grasp water quality dynamic changes in lake eutrophication through phytoplankton parameters
Utilizing machine learning models to grasp water quality dynamic changes in lake eutrophication through phytoplankton parameters
Yong Fang,Ruting Huang,3 Authors,Xianyang Shi
2024 · DOI: 10.1007/s11783-025-1934-6
Frontiers of Environmental Science and Engineering · 7 Citations
TLDR
Five tree-based ML models developed using the latest data on hydrological, water quality, and meteorological parameters obtained high accuracy in predicting the total nitrogen/total phosphorus ratio (TN/TP) and phytoplankton parameters, especially the Shannon index (H′).