On the use of neural networks to evaluate groundwater levels in fractured media

This paper evaluates the feasibility of using artificial neural network (ANN) methodology for estimating the groundwater level in some piezometers implanted in unconfined chalky aquifer of Northern France. These aquifers are the most susceptible to depletion and contamination, with the recharge rate...

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Vydáno v:	Journal of hydrology (Amsterdam) Ročník 307; číslo 1; s. 92 - 111
Hlavní autoři:	Lallahem, S., Mania, J., Hani, A., Najjar, Y.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 09.06.2005 Elsevier Science Elsevier
Témata:	algorithms ANN aquifers Backpropagation algorithm Chalk Earth sciences Earth, ocean, space Exact sciences and technology Fractured media France Groundwater Hydrogeology hydrologic models Hydrology. Hydrogeology neural networks simulation models water table France Somme France Western Europe Fractured media ANN Backpropagation algorithm Chalk Groundwater algorithms models carbonate rocks Europe neural networks ground water water table digital simulation contamination fractured environment sedimentary rocks aquifers chalk piezometry unconfined aquifers
ISSN:	0022-1694, 1879-2707
On-line přístup:	Získat plný text
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