Performance of an artificial neural network model for simulating saltwater intrusion process in coastal aquifers when training with noisy data
Bhattacharjya, Rajib Kumar, Datta, Bithin, and Satish, Mysore G. (2009) Performance of an artificial neural network model for simulating saltwater intrusion process in coastal aquifers when training with noisy data. KSCE Journal of Civil Engineering, 13 (3). pp. 205-215.
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This paper evaluates the performance of an Artificial Neural Networks (ANN) model for approximating density depended saltwater intrusion process in coastal aquifer when the ANN model is trained with noisy training data. The data required for training, testing and validation of the ANN model are generated using a numerical simulation model. The simulated data, consisting of corresponding sets of input and output patterns are used for training a multilayer perception using back-propagation algorithm. The trained ANN predicts the concentration at specified observation locations at different time steps. The performance of the ANN model is evaluated using an illustrative study area. These evaluation results show the efficient predicting capabilities of an ANN model when trained with noisy data. A comparative study is also carried out for finding the better transfer function of the artificial neuron and better training algorithms available in Matlab for training the ANN model.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||artificial neural networks; saltwater intrution process; groundwater; noisy data; approximation model|
|Date Deposited:||21 Apr 2010 23:59|
|FoR Codes:||09 ENGINEERING > 0907 Environmental Engineering > 090702 Environmental Engineering Modelling @ 50%
09 ENGINEERING > 0905 Civil Engineering > 090509 Water Resources Engineering @ 50%
|SEO Codes:||96 ENVIRONMENT > 9606 Environmental and Natural Resource Evaluation > 960604 Environmental Management Systems @ 25%
96 ENVIRONMENT > 9609 Land and Water Management > 960999 Land and Water Management of Environments not elsewhere classified @ 25%
96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960506 Ecosystem Assessment and Management of Fresh, Ground and Surface Water Environments @ 50%
|Citation Count from Scopus||