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Water Resources Management

Erschienen in:

13.11.2018

Multilayer Feed Forward Models in Groundwater Level Forecasting Using Meteorological Data in Public Management

verfasst von: Georgios N. Kouziokas, Alexander Chatzigeorgiou, Konstantinos Perakis

Erschienen in: Water Resources Management | Ausgabe 15/2018

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Abstract

Managing the groundwater resources is very vital for human life. This research proposes a methodology for predicting the groundwater levels which can be very valuable in water resources management. This study investigates the application of multilayer feed forward network models for forecasting the groundwater values in the region of Montgomery country in Pennsylvania. Multiple training algorithms and network structures were investigated to develop the best model in order to forecast the groundwater levels. Several multilayer feed forward models were created in order to be tested for their performance by changing the network topology parameters so as to find the optimal prediction model. The forecasting models were developed by applying different structures regarding the number of the neurons in every hidden layer and the number of the hidden network layers. The final results have shown a very good forecasting accuracy of the predicted groundwater levels. This research can be very valuable in water resources and environmental management.

Vorheriger Artikel An Analytical Solution of Groundwater Flow in Wedge-shaped Aquifers with Estuarine Boundary Conditions

Nächster Artikel Pareto Optimization of Water Resources Using the Nexus Approach

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Titel: Multilayer Feed Forward Models in Groundwater Level Forecasting Using Meteorological Data in Public Management
verfasst von: Georgios N. Kouziokas
Alexander Chatzigeorgiou
Konstantinos Perakis
Publikationsdatum: 13.11.2018
Verlag: Springer Netherlands
Erschienen in: Water Resources Management / Ausgabe 15/2018
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI: https://doi.org/10.1007/s11269-018-2126-y

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