• Deepak Mangal
• Suppawit Glawkate
• Lakhshan Sarvanan
• Pragati Prashant Tolamatti

Water quality index (WQI) is widely used to assess and classify groundwater and surface water quality and plays an important role in water resource management. In recent decades, artificial intelligence (AI) in the form of machine learning models has been applied to solve various environmental engineering problems, such as water quality modelling. Machine learning models represent a major innovation in research for monitoring and controlling a variety of engineering processes, using their algorithms. The proposed models have been evaluated and tested using certain statistical parameters. The results have revealed that the Random Forest algorithm has achieved the highest accuracy level compared to other machine learning models like decision tree, MLP and gradient boosting.

Artificial Intelligence, Machine Learning, Water Quality Index, Model comparison

"Machine Learning Algorithms Comparative Study", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.k189-k198, April-2023, Available :http://www.jetir.org/papers/JETIR2304A27.pdf

"Machine Learning Algorithms Comparative Study", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppk189-k198, April-2023, Available at : http://www.jetir.org/papers/JETIR2304A27.pdf