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 |
Groundwater is an essential source of water for the domestic, agricultural, and industrial sectors. Due to over-extraction, the trend of groundwater levels declining continues steadily. So, there is a need to monitor the behavior of fluctuations and the prediction of groundwater levels for making effective policies and management practices that support sustainable groundwater usage. In this study, fluctuations in the groundwater level of the Veppanthattai block observation wells were forecasted using Artificial Neural Networks (ANN). Multilayer Feed Forward Neural Network (FFNN) was selected for the network architecture and Levenberg- Marquardt (LM)algorithm was used for training the data. The performance of the network was evaluated by Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) and Theil’s U and the optimal networks of observation wells were discussed.
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