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

Volumn 13, Issue 3, 2009, Pages 205-215

  Bhattacharjya, Rajib Kumar ^a   Datta, Bithin ^b   Satish, Mysore G ^c  

^a INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

^c DALHOUSIE UNIVERSITY   (Canada)

Author keywords

Approximation model; Artificial neural networks; Groundwater; Noisy data; Saltwater intrusion process

Indexed keywords

APPROXIMATION MODEL; ARTIFICIAL NEURAL NETWORK MODELS; ARTIFICIAL NEURAL NETWORKS; ARTIFICIAL NEURONS; BACK-PROPAGATION ALGORITHMS; COASTAL AQUIFERS; COMPARATIVE STUDIES; DIFFERENT TIME STEPS; EVALUATION RESULTS; INPUT AND OUTPUTS; MULTI-LAYER PERCEPTIONS; NOISY DATA; NUMERICAL SIMULATION MODELS; SALTWATER INTRUSION PROCESS; SIMULATED DATUM; STUDY AREAS; TRAINING ALGORITHMS; TRAINING DATUM;

AQUIFERS; BACKPROPAGATION; GROUNDWATER RESOURCES; HYDROGEOLOGY; MATLAB; SALT WATER INTRUSION;

NEURAL NETWORKS;

EID: 65449135526     PISSN: 12267988     EISSN: 19763808     Source Type: Journal    
DOI: 10.1007/s12205-009-0205-6     Document Type: Article

References (25)

1. W. M. Alley 1986 Regression approximation for transport model constraint sets in combined aquifer simulation-optimization studies Water Resour. Res. 22 4 581 586
2. A. H. Aly R. C. Peralta 1999 Optimal design of aquifer cleanup systems under uncertainty using a neural network and genetic algorithms Water Resour. Res. 35 8 2523 2532
3. Bear, J., Cheng, A. H. D., Sorek, S., Ouazar, D., and Herrera, I. (1999). Seawater Intrusion in Coastal Aquifers - Concepts, Methods and Practices, in Theory and Application of Transport in Porous Media, Edited by J. Bear. Kluwer Academic Publishers, Dordrecht, p. 625.
4. R. K. Bhattacharjya B. Datta 2005 Optimal management of coastal aquifers using link simulation optimization approach J. Water Resources Management 19 3 295 320
5. R. K. Bhattacharjya B. Datta M. G. Satish 2007 Artificial neural networks approximation of density dependent saltwater intrusion process in coastal aquifers Journal of Hydrologic Engineering 12 3 273 282
6. S. J. Burian S. R. Durrans S. J. Nix R. E. Pitt 2001 Training of artificial neural networks to perform rainfall disaggregation J. of Hydrologic Engineering 6 1 43 51
7. J. M. Cheng C. X. Chen 2001 Three-dimensional modeling of density-dependent saltwater intrusion in multilayered coastal aquifers in Jahe river basin, Shandong province, China Ground Water 39 1 137 143
8. P. Coulibaly F. Anctil B. Bobçe 2000 Daily reservoir inflow forecasting using artificial neural networks with stopped training approach J. of Hydrology 230 244 257
9. A. Das B. Datta 2000 Optimization based solution of density dependent seawater intrusion in coastal aquifers J. of Hydrologic Engg. 5 1 82 89
10. M. S. Ejaz R. C. Peralta 1985 Modeling for optimal management of agricultural and domestic wastewater loading to streams Water Resour. Res. 31 4 1087 1096
11. Hassoun, M. H. (1999). Fundamentals of Artificial Neural Networks, Prentice Hall of India Pvt. Ltd., New Delhi, pp. 226-230.
12. K. Hsu V. H. Gupta S. Sorooshian 1995 Artificial neural network modeling of the rainfall-runoff process Water Resources Research 31 10 2517 2530
13. A. Jain A. Kumar 2006 An evaluation of artificial neural network technique for the determination of infiltration model parameters J. Soft Computing 6 3 272 282
14. A. Jain S. Srinivasulu R. K. Bhattacharjya 2005 Determination of an optimal unit pulse response function using real-coded genetic algorithm J. Hydrology 303 1-4 199 214
15. V. M. Johnson L. L. Rogers 2000 Accuracy of neural network approximations in simulation-optimization J. of Water Resour. Planning and Management 126 2 48 56
16. A. Korre S. Durucan C. E. Imrie 2000 River flow prediction using artificial neural networks: Generalized beyond calibration range J. of Hydrology 233 138 153
17. L. J. Lefkoff S. M. Gorelick 1990 Simulating physical processes and economic behavior in saline, irrigated agriculture: Model development Water Resour. Res. 26 7 1359 1369
18. Lin, H. J., Rechards, D. R., Talbot, C. A., Yeh, G. T., Cheng, J. R., Cheng, H. P., and Jones, N. L. (1997). A three-dimensional finite element computer model for simulating density-dependent flow and transport in variable saturated media: Version 3.1, U.S. Army Engg. Research and Development Center. Vicksburg, M.S. 1997.
19. S. Y. Liong W. H. Lim G. N. Paudyal 2000 River stage forecasting in bangladesh: Neural network approach J. of Computing in Civil Engineering 4 1 1 8
20. J. Morshed J. J. Kaluarachchi 1998 Application of artificial neural networks and genetic algorithms in flow and transport simulation Adv. in Water Resour. 22 2 145 158
21. L. L. Rogers F. U. Dowla 1994 Optimization of ground water remediation using artificial neural networks and parallel solute transport modeling Water Resour. Res. 30 2 457 481
22. rd international conference finite element water resources. University of Mississippi, Oxford, Miss. 1980.
23. M. M. Sherif V. P. Singh A. M. Amer 1988 A two-dimensional finite element model for dispersion (2D-FED) in coastal aquifer J. of hydrology 103 11 36
24. Todd, D. K. (1980). Groundwater Hydrology, John Wiley & Sons. Singapore.
25. R. Willis B. A. Finney 1988 Planning model for optimal control of saltwater intrusion J. of Water Resour. Plng. and Mgmt. 114 2 163 178