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Predictive modellingof post-monsoongroundwater qualityin Telangana usingmachine learningtechniques Olentsova JuliaKukartsev VladislavOrlov Vasiliy2024 год

Predictive modelling of post-monsoon groundwater quality in Telangana using machine learning techniques : доклад, тезисы доклада
доклад, тезисы доклада, статья из сборника материалов конференций

Дополнительные ссылки: eLibrary · Источник статьи
База данных: Каталог библиотеки СФУ
Библиографическое описание: Predictive modelling of post-monsoon groundwater quality in Telangana using machine learning techniques : доклад, тезисы доклада / J. J. Olentsova [et al.]. - [S. l. : s. n.], 2024. - Текст : непосредственный // BIO WEB OF CONFERENCES : EBWFF 2024 - International Scientific Conference Ecological and Biological Well-Being of Flora and Fauna / EBWFF 2024 - International Scientific Conference Ecological and Biological Well-Being of Flora and Fauna (2023 ; 22.05 - 25.05 ; Blagoveschensk). - Les Ulis, 2024. - 116. - P. 03021. - 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 parameters: 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>
Год издания: 2024
Авторы: Olentsova Julia , Kukartsev Vladislav , Orlov Vasiliy , Semenova Evgenia , Pinchuk Ivan
Издательство: Les Ulis
Источник: BIO WEB OF CONFERENCES
Выпуск: 116
Мероприятие: EBWFF 2024 - International Scientific Conference Ecological and Biological Well-Being of Flora and Fauna (Blagoveschensk, 2023 ; 22.05 - 25.05)
Номера страниц: 03021
Держатель оригинала документа: Bauman Moscow State Technical University, Krasnoyarsk State Agrarian University, Reshetnev Siberian State of Science and Technology, Siberian federal university, SPE «Radiosvyaz» JSC, ERP department
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Твёрдая копия издания отсутствует в фонде библиотеки

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