Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/3073
Title: Groundwater Level Simulation Using Artificial Neural Network in Southeast, Punjab, India
Authors: Lohani, A. K.
Krishan, Gopal
Keywords: Artificial neural networks
Groundwater level forecasting
South-east Punjab- Aquifer exploitation
Issue Date: 2015
Publisher: SCIAEON
Citation: J Geol Geosci 2015, 4:3
Abstract: This paper presents an efficient and stable artificial neural network (ANN) model for predicting groundwater level in south-east Punjab, India. After improving the model accuracy using different types of network architectures and training algorithms, it has been observed that best results can be achieved with a standard feed forward neural network trained with the Levenberg–Marquardt algorithm. Good estimation of groundwater level can be achieved by designing distinct networks for different sites and ANN method has been found to forecast groundwater level in Faridkot, Ferozepur, Ludhiana and Patiala districts of Punjab, India with reasonable accuracy
URI: http://117.252.14.250:8080/jspui/handle/123456789/3073
Appears in Collections:Research papers in International Journals

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