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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
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Original Research Articles                      Volume : 12, Issue:6, June, 2023

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

Int.J.Curr.Microbiol.App.Sci.2023.12(6): 216-225
DOI: https://doi.org/10.20546/ijcmas.2023.1206.026


Uncertainty of the Ground Water Fluctuation Based on ANN Approach
Shashindra Kumar Sachan1*, Arpan Sherring2 and Derrick M. Denis3
1Department of Agricultural Engineering, Chandrashekhar Azad University of Agriculture and Technology, Kanpur, Uttar Pradesh-208002, India
2Department of Irrigation and Drainage Engineering, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, Uttar Pradesh-211007, India

*Corresponding author
Abstract:

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.


Keywords: Forecasting, Uncertainty analysis, Groundwater level fluctuations

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How to cite this article:

Shashindra Kumar Sachan, Arpan Sherring and Derrick M. Denis. 2023. Uncertainty of the Ground Water Fluctuation Based on ANN Approach.Int.J.Curr.Microbiol.App.Sci. 12(6): 216-225. doi: https://doi.org/10.20546/ijcmas.2023.1206.026
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

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