Abstract
The main aim of this research article is to compare the different algorithms of artificial neural networks and for prediction of groundwater-level feed-forward back propagation networks were applied for Baberu Block of Banda Districts, which comes under Yamuna River Basin. An optimal design is completed with four different algorithms such as Levenberg–Marquardt, Gradient Descent, Scaled Conjugate Gradient and Bayesian Regularization. The data regarding training of ANN is obtained from recharge and discharge data while groundwater level data was used for output layer. After comparison with different algorithms, the best algorithm is Levenberg–Marquardt algorithm.
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The authors would like to specially thank to the Banda irrigation department to provide all necessary data.
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Asghar Moeeni, S., Sharif, M., Ahsan, N., Iqbal, A. (2021). Simulation of Groundwater level by Artificial Neural Networks of Parts of Yamuna River Basin. In: Bajpai, M.K., Kumar Singh, K., Giakos, G. (eds) Machine Vision and Augmented Intelligence—Theory and Applications. Lecture Notes in Electrical Engineering, vol 796. Springer, Singapore. https://doi.org/10.1007/978-981-16-5078-9_32
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