Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: EBWFF 2024 - International Scientific Conference Ecological and Biological Well-Being of Flora and Fauna; Blagoveschensk; Blagoveschensk
Год издания: 2024
Идентификатор DOI: 10.1051/bioconf/202411603021
Аннотация: <jats:p>Groundwater quality is vital for public health, agriculture, and industry, especially in regions like Telangana, India. This study analyses and predicts post-monsoon 2020 groundwater quality using data from the Telangana State Groundwater Department. We employed Linear Regression and Random Forest Regression to predict key Показать полностьюparameters: pH and Total Dissolved Solids (TDS). Exploratory data analysis revealed significant correlations, such as between TDS and Electrical Conductivity (E.C). The Linear Regression model for TDS performed exceptionally well, with an R<jats:sup>2</jats:sup> of 0.985, while the Random Forest model also showed strong results. However, both models exhibited moderate accuracy in predicting pH. The study demonstrates the effectiveness of machine learning models in predicting groundwater quality, offering valuable tools for groundwater management. These findings can aid policymakers and environmental managers in making informed decisions to safeguard water resources.</jats:p>
Журнал: BIO WEB OF CONFERENCES
Выпуск журнала: 116
Номера страниц: 03021
Место издания: Les Ulis