Choosing between linear and nonlinear models and avoiding overfitting for short and long term groundwater level forecasting in a linear system-Reference-Cited by-同舟云学术

Choosing between linear and nonlinear models and avoiding overfitting for short and long term groundwater level forecasting in a linear system

Published:2019-11 Issue: Volume:578 Page:124015
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Zanotti Chiara,Rotiroti Marco,Sterlacchini Simone,Cappellini Giacomo,Fumagalli Letizia,Stefania Gennaro A.,Nannucci Marco S.,Leoni Barbara,Bonomi Tullia

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference61 articles.

1. A wavelet neural network conjunction model for groundwater level forecasting;Adamowski;J. Hydrol.,2011

2. Comparison of multivariate regression and artificial neural networks for peak urban water-demand forecasting: evaluation of different ANN learning algorithms;Adamowski;J. Hydrol. Eng.,2010

3. Groundwater head sampling based on stochastic analysis;Ahn;Water Resour. Res.,1997

4. Forecasting of groundwater level in hard rock region using artificial neural network;Banerjee;Environ. Geol.,2009

5. Neural Network ToolboxTM User’s Guide;Beale,2016

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