Modeling the Neuman's well function by an artificial neural network for the determination of unconfined aquifer parameters

DOI10.1007/S10596-018-9742-8zbMath1401.86005OpenAlexW2803667854MaRDI QIDQ1787661

Nozar Samani, Tahereh Azari

Publication date: 5 October 2018

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-018-9742-8

zbMATH Keywords

pumping testprincipal component analysis (PCA)multi-layer perceptronaquifer parameterswell function

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Inverse problems in geophysics (86A22) Neural nets and related approaches to inference from stochastic processes (62M45)

Cites Work

• Multilayer feedforward networks are universal approximators
• Advances in Neural Networks – ISNN 2005
• A logical calculus of the ideas immanent in nervous activity
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