Predicting methane solubility in water and seawater by machine learning algorithms: Application to methane transport modeling.

Taherdangkoo, Reza; Liu, Quan; Xing, Yixuan; Yang, Huichen; Cao, Viet; Sauter, Martin; Butscher, Christoph

Taherdangkoo, Reza; Liu, Quan; Xing, Yixuan; Yang, Huichen; Cao, Viet; Sauter, Martin; Butscher, Christoph.

Afiliación

Taherdangkoo R; TU Bergakademie Freiberg, Institute of Geotechnics, Gustav-Zeuner-Str. 1, 09599 Freiberg, Germany. Electronic address: reza.Taherdangkoo@ifgt.tu-freiberg.de.
Liu Q; Department of Applied Geology, Geosciences Center, University of Göttingen, Goldschmidtstr. 3, 37077 Göttingen, Germany.
Xing Y; Department of Applied Geology, Geosciences Center, University of Göttingen, Goldschmidtstr. 3, 37077 Göttingen, Germany.
Yang H; Department of Applied Geology, Geosciences Center, University of Göttingen, Goldschmidtstr. 3, 37077 Göttingen, Germany.
Cao V; Faculty of Natural Sciences, Hung Vuong University, Nguyen Tat Thanh Str., Viet Tri, 35120 Phu Tho, Viet Nam.
Sauter M; Department of Applied Geology, Geosciences Center, University of Göttingen, Goldschmidtstr. 3, 37077 Göttingen, Germany.
Butscher C; TU Bergakademie Freiberg, Institute of Geotechnics, Gustav-Zeuner-Str. 1, 09599 Freiberg, Germany.

J Contam Hydrol ; 242: 103844, 2021 10.

Article en En | MEDLINE | ID: mdl-34111717

Asunto(s)

Metano; Agua; Algoritmos; Teorema de Bayes; Aprendizaje Automático; Agua de Mar; Solubilidad

Palabras clave

Equation of state; Groundwater; Machine learning; Methane; Seawater; Solubility

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Agua / Metano Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Contam Hydrol Asunto de la revista: TOXICOLOGIA Año: 2021 Tipo del documento: Article Pais de publicación: Países Bajos

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