AIMC Topic: Water Pollutants, Radioactive
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Prediction of anthropogenic I in the South China Sea based on machine learning.
Journal of environmental radioactivity
May 2, 2025
With the rapid increase in the number of nuclear power plants along the China coast and the potential for releases of radioactive substances to marine ecosystems, it is important to investigate and predict the dispersion of radionuclides in the seas ...
Machine learning models for water safety enhancement.
Scientific reports
Jan 30, 2025
Humans encounter both natural and artificial radiation sources, including cosmic rays, primordial radionuclides, and radiation generated by human activities. These radionuclides can infiltrate the human body through various pathways, potentially lead...
Use of machine learning and deep learning to predict particulate Cs concentrations in a nuclearized river.
Journal of environmental radioactivity
Sep 15, 2023
Cesium-137, discharged by nuclear installations under normal operations and deposited in watersheds following atmospheric testing and accidents (i.e. Chernobyl, Fukushima …), has been studied for decades. Thus, modelling of Cs concentration in rivers...
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