DSpace Repository

Groundwater Level Simulation Using Artificial Neural Network in Southeast, Punjab, India

Show simple item record

dc.contributor.author Lohani, A. K.
dc.contributor.author Krishan, Gopal
dc.date.accessioned 2019-07-11T10:03:08Z
dc.date.available 2019-07-11T10:03:08Z
dc.date.issued 2015
dc.identifier.citation J Geol Geosci 2015, 4:3 en_US
dc.identifier.uri http://117.252.14.250:8080/jspui/handle/123456789/3073
dc.description.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 en_US
dc.language.iso en en_US
dc.publisher SCIAEON en_US
dc.subject Artificial neural networks en_US
dc.subject Groundwater level forecasting en_US
dc.subject South-east Punjab- Aquifer exploitation en_US
dc.title Groundwater Level Simulation Using Artificial Neural Network in Southeast, Punjab, India en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account