The Use of NARX Neural Networks to Forecast Daily Groundwater Levels-Reference-Cited by-同舟云学术

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The Use of NARX Neural Networks to Forecast Daily Groundwater Levels

Published:2017-03 Issue:5 Volume:31 Page:1591-1603
ISSN:0920-4741
Container-title:Water Resources Management
language:en
Short-container-title:Water Resour Manage

Author:

Guzman Sandra M.,Paz Joel O.,Tagert Mary Love M.

Funder

National Institute of Food and Agriculture

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11269-017-1598-5.pdf

Reference46 articles.

1. Abdulkadir SJ, Yong S-P (2015) Scaled UKF–NARX hybrid model for multi-step-ahead forecasting of chaotic time series data. Soft Comput 19:3479–3496. doi: 10.1007/s00500-015-1833-z

2. Adeloye A, De Munari A (2006) Artificial neural network based generalized storage–yield–reliability models using the Levenberg–Marquardt algorithm. J Hydrol 326:215–230

3. Anderson MG (2005) Encyclopedia of hydrological sciences vol 1. Chichester; Hoboken: J. Wiley

4. Antonopoulos VZ, Georgiou PE, Antonopoulos ZV (2015) Dispersion coefficient prediction using empirical models and ANNs. Environ Process 2:379–394. doi: 10.1007/s40710-015-0074-6

5. Arthur JK (2001) Hydrogeology, model description, and flow analysis of the Mississippi River alluvial aquifer in northwestern Mississippi, vol 1

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