Hybrid Model Fusion: Enhancing Water Quality Prediction using Ensemble Modelling

Water is an essential natural resource, vital for life, making it important to ensure its quality for our safety. Traditional methods for checking water quality, like laboratory tests, can take time to provide results. Machine learning (ML) offers a faster and potentially more accurate way to predict water quality. This article explores how machine learning can be used to predict water quality. It looks at a range of ML techniques such as support vector machines, decision trees, and clustering methods, and how they can help model various aspects of water quality. These aspects include pH levels, dissolved oxygen, turbidity (how cloudy the water is), and contamination from pollutants. The article also talks about the challenges in this field and suggests areas for future research. By the use of machine learning in water quality prediction can lead to better and quicker results, aiding in effective water management and conservation.