Comparative analysis of machine learning models for predicting water quality index in Dhaka’s rivers of Bangladesh
Islamic University of Technology · Bangladesh University of Engineering and Technology · +3 more institutions
Abstract
The pollution in Dhaka's navigable waterways, including the Buriganga, Balu, Tongi Khal, and Turag rivers, is a significant concern due to rapid industrial and urban expansion. Industrial discharges, domestic sewage and inadequate waste management are the primary sources of this pollution, degrading water quality and threatening aquatic ecosystems. This study aimed to predict the Water Quality Index (WQI) of these rivers using fourteen machine learning (ML) models: Decision Tree Regression, Linear Regression, Ridge Regression, Stochastic Gradient Descent (SGD) Regressor, Extreme Gradient Boosting (XGB) Regressor, Light Gradient Boosting Machine (GBM) Regressor, Elastic Net Regressor, Support Vector Regression…
Citation impact
- FWCI
- 32.44
- Percentile
- 100%
- References
- 107
Authors
9- MNMaliha NishatCorresponding
Islamic University of Technology
- MHMd. Habibur Rahman Bejoy Khan
Islamic University of Technology
- TATahmeed Ahmed
Islamic University of Technology
- SASk Arafat Hossain
Bangladesh University of Engineering and Technology
- AAAmimul Ahsan
Islamic University of Technology, Swinburne University of Technology
Topics & keywords
- Water quality
- Index (typography)
- Ecotoxicology
- Environmental science
- Statistics
- Mathematics
- Toxicology
- Ecology
- Clean water and sanitation