National Academy of Agricultural Sciences (NAAS)
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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
This study pursues to determine the accuracy of the groundwater level fluctuations forecasted at the Kanpur district of India using artificial neural networks (ANNs). The results indicated that performance of multilayer perceptron (MLP) based neural network (M-3, architecture 4-18-1) is satisfactory in the groundwater level fluctuations forecasting. The performance assessment shows that the MLP model performs significantly better. The uncertainty analysis shows that, input of Absent- RF and Absent- ERF, Absent- GWt-1, and Absent- GWt-5 were found more sensitive for GWFs forecasting and can’t ignore as input combination & input of Absent- WS and RH were found less sensitive for GWFs forecasting and may be discarded as input combination for GWFs forecasting.
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