Prediction of groundwater quality using efficient machine learning technique.

Singha, Sudhakar; Pasupuleti, Srinivas; Singha, Soumya S; Singh, Rambabu; Kumar, Suresh

Singha, Sudhakar; Pasupuleti, Srinivas; Singha, Soumya S; Singh, Rambabu; Kumar, Suresh.

Afiliación

Singha S; Department of Civil Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, Jharkhand, India.
Pasupuleti S; Department of Civil Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, Jharkhand, India. Electronic address: srinivas@iitism.ac.in.
Singha SS; Department of Civil Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, Jharkhand, India.
Singh R; Exploration Department, Central Mine Planning and Design Institute Limited, Bilaspur, 495006, Chhattisgarh, India.
Kumar S; Central Ground Water Board, Patna, 800001, Bihar, India.

Chemosphere ; 276: 130265, 2021 Aug.

Article en En | MEDLINE | ID: mdl-34088106

Asunto(s)

Agua Subterránea; Contaminantes Químicos del Agua; India; Aprendizaje Automático; Contaminantes Químicos del Agua/análisis; Calidad del Agua

Palabras clave

Entropy weight-based groundwater quality index; Machine learning algorithms; Prediction models; Variable importance

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Químicos del Agua / Agua Subterránea Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies País/Región como asunto: Asia Idioma: En Revista: Chemosphere Año: 2021 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido

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