Modeling haloketones in drinking water using conformable neural networks: a case study of Jinhua, China

Key Points

• Haloketones in drinking water were effectively modeled using neural networks, improving prediction accuracy.
• The study utilized a dataset from Jinhua, China, to assess levels of haloketones in the water supply.
• Neural networks provided insights into the distribution and concentrations of these contaminants efficiently.
• Findings may enable better management of drinking water quality and safety regarding haloketone levels.