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[1]
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Use of meta-heuristic approach in the estimation of aquifer's response to climate change under shared socioeconomic pathways
Groundwater for Sustainable Development,
2023
DOI:10.1016/j.gsd.2022.100882
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[2]
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Evaluation of groundwater level, quality and recharge: a case study of Can Tho City, Viet Nam
Vietnam Journal of Science and Technology,
2023
DOI:10.15625/2525-2518/16426
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[3]
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Estimating of aqueduct water withdrawal via a wavelet-hybrid soft-computing approach under uniform and non-uniform climatic conditions
Environment, Development and Sustainability,
2023
DOI:10.1007/s10668-022-02265-y
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[4]
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Enhancement groundwater level prediction using hybrid ANN-HHO model: case study (Shabestar Plain in Iran)
Arabian Journal of Geosciences,
2023
DOI:10.1007/s12517-023-11584-x
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[5]
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A deep neural multi-model ensemble (DNM2E) framework for modelling groundwater levels over Kerala using dynamic variables
Stochastic Environmental Research and Risk Assessment,
2023
DOI:10.1007/s00477-023-02570-6
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[6]
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Estimating of aqueduct water withdrawal via a wavelet-hybrid soft-computing approach under uniform and non-uniform climatic conditions
Environment, Development and Sustainability,
2022
DOI:10.1007/s10668-022-02265-y
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[7]
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Modeling aquifer hydrograph: performance review of conceptual MODFLOW and simulator models
Arabian Journal of Geosciences,
2020
DOI:10.1007/s12517-020-5230-2
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[8]
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Assessment of artificial neural network models based on the simulation of groundwater contaminant transport
Hydrogeology Journal,
2020
DOI:10.1007/s10040-020-02180-4
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[9]
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Artificial Neural Network Optimized with a Genetic Algorithm for Seasonal Groundwater Table Depth Prediction in Uttar Pradesh, India
Sustainability,
2020
DOI:10.3390/su12218932
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[10]
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Artificial Neural Network Optimized with a Genetic Algorithm for Seasonal Groundwater Table Depth Prediction in Uttar Pradesh, India
Sustainability,
2020
DOI:10.3390/su12218932
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[11]
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Groundwater level forecasting using soft computing techniques
Neural Computing and Applications,
2019
DOI:10.1007/s00521-019-04234-5
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