A Reliable Method of Predicting Water Quality Using Supervised Machine Learning Model
- Title
- A Reliable Method of Predicting Water Quality Using Supervised Machine Learning Model
- Creator
- Nanjundan P.; George J.P.; Vij A.
- Description
- Water contributes to around 70% of the world's exterior and is perhaps the primary source essential to supporting life. The rapid growth of urban and industrial geographies has prompted a disintegration of the quality of water at a concerning pace, bringing about nerve-racking sicknesses. Water quality has been expectedly assessed through costly and tedious lab and measurable examinations, which render the contemporary thought of continuous observing disputable. The disturbing results of helpless water quality require an elective strategy, which is speedier and more economical. With this inspiration, this exploration investigates a progression of administered AI calculations to appraise the Water Quality Index (WQI), which acts as a unique attribute to express the generic nature of water. The proposed system utilizes multiple info boundaries, specifically, temperature, pH, dissolved O2 concentration, and all-out broken down molecules. Of the multitude of utilized regression calculations and slope boosting, the water quality index can be expected most productively, with an MSE of 0.27. The propositioned study accomplishes acceptable precision by utilizing a minimum number of features to improve the chances of it getting implemented progressively in water quality recognition frameworks. 2022 IEEE.
- Source
- IEEE International Conference on Data Science and Information System, ICDSIS 2022
- Date
- 2022-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Gradient boosting; Indian rivers; Monitoring expert system; Regression Analysis Supervised machine learning; Water quality index
- Coverage
- Nanjundan P., Christ University, India; George J.P., Christ University, India; Vij A., Bajaj Allianz Life, Department of Analytics, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-166549801-2
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Nanjundan P.; George J.P.; Vij A., “A Reliable Method of Predicting Water Quality Using Supervised Machine Learning Model,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/20215.