ANN, SA and GA application in Groundwater Hydrology
Evolutionary Algorithms in Parameter Estimation of Confined and Unconfined Aquifers
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Utilisation of groundwater is steadily growing in many parts of the world to cope up with the increasing demand in various water user sectors. However scientific use of the precious groundwater calls for proper planning which involve modeling of the system. Recently for groundwater system planning and management use of soft computing tools is growing since these are found better than conventional numerical optimisation technique. Since groundwater problems involve non-linear objective function, their gradient with respect to parameters cause numerical instability. Simulated annealing, artifici...
Utilisation of groundwater is steadily growing in many parts of the world to cope up with the increasing demand in various water user sectors. However scientific use of the precious groundwater calls for proper planning which involve modeling of the system. Recently for groundwater system planning and management use of soft computing tools is growing since these are found better than conventional numerical optimisation technique. Since groundwater problems involve non-linear objective function, their gradient with respect to parameters cause numerical instability. Simulated annealing, artificial neural network and genetic algorithms help in assessment of near global optimal solutions which are meaningful for real system simulation. Synthetic aquifer problems considered in the presented book are particularly useful to demonstrate the application of SA, ANN and GA to assess the aquifer system parameters. However when properly understood from the given applications these can be meaningfully applied to real problems.
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