Transport of contaminants in underground waters using artificial neural networks;Transporte de contaminantes en aguas subterráneas mediante Redes Neuronales Artificiales

Informacion Tecnologica

Volumn 21, Issue 5, 2010, Pages 79-86

  García, Ignacio ^a   Rodríguez, José G ^a   López, Felipe ^a   Tenorio, Yenisse M ^a  

^a INSTITUTO POLITÉCNICO NACIONAL   (Mexico)

Author keywords

Artificial neural networks; Backpropagation; Pollutants transport; Textural classes

Indexed keywords

EID: 78149350204     PISSN: 07168756     EISSN: 07180764     Source Type: Journal    
DOI: 10.1612/inf.tecnol.4349it.09     Document Type: Article

References (28)

1. Altunkaynak, A.; Forecasting surface water level fluctuations of lake van by artificial neural networks, Water Resour Manage". 21, 399-408 (2006).
2. Bedient, P. B., H. S. Rifai y C. J. Newell; Ground water contamination: transport and remediation. Prentice Hall (1994)
3. 10, NO2, CO I the urban area of Palermo, Italy, Atmospheric Environment". 41, 2967-2995 (2007).
4. Chao, L.L.; Introducción a la estadística; CECSA (1998).
5. Charbeneau R. J.; Groundwater Hydraulics and Pollutant transport. Prentice Hall (2000).
6. Demuth, H, M. Beale y M. Hagan; Neural Networks Toolbox. For Use with MATLAB. User's Guide Versión 4. The MathWortks (2005).
7. a ed., Editorial Ra- Ma (2001).
8. Freeman, J. A. y Skapura D. M; Redes Neuronales: algoritmos, aplicaciones y técnica de programación. Díaz de Santos, 423 p. (1993).
9. García, I, A. Marbán, Y. M. Tenorio y J. G. Rodriguez; Pronóstico de la Concentración de Ozono en Guadalajara- México usando Redes Neuronales Artificiales, Información Tecnológica, 19(3), 89-96 (2008).
10. Garcia, L. A., A. Shigidi; Using neural networks for parameter estimation in ground water, Journal of Hydrology 318, 215-231(2006).
11. Goethals, P. L. M., y otros cuatro autores; Applications of artificial neural networks predicting macroinvertebrates in freshwaters, Aquat. Ecol., 41, 491-508 (2007).
12. 10 hourly concentrations, in the Greater Area of Athens, Greece, Atmospheric Environment". 40, 1216-1229 (2006).
13. Gurney, K.; An introduction to neural networks, CRC PRESS (2003).
14. Helle, H. B., Alpana B., Bjørn U.; Porosity and permeability prediction from wireline logs using artificial neural networks: a North Sea case study, Geophysical Prospecting". 49, 431-444 (2001).
15. Kuo, Y., Chen-Wuing L., Kao-Hung L.; Evaluation of the ability of an artificial neural network model to assess the variation of groundwater quality in an area of blackfoot disease in Taiwan, Water Research". 38, 148-158 (2003).
16. Lek, S. y Guegan J. F; Artificial Neural Networks. Application to Ecology and Evolution, Springer, pp. 3-25 (2000).
17. López, F.; Contaminación del Suelo por un Contaminante Conservativo, Tesis de Maestría, UNAM, D. F., México (1980).
18. Mehrotra, K., C. K. Mohar y S. Ranka; Elements of Artificial Neural Networks, The MIT Press Broadford (1997).
19. Mora, H. J; Modelo Matemático unidimensional de dispersión de contaminantes en aguas subterráneas, Tesis de maestría, IPN-ESIA TICOMAN, D. F., México (1999).
20. Ogata, A. y R. B. Banks; A Solution of the Differential Equation of longitudinal Dispersion in Porous Media. United States Government Printing Office. Paper 411-A (1961).
21. 10 forecasting, Atmospheric Environment". 40, 2845-2851 (2006).
22. Rodríguez, J. G. y M. Y, Tenorio; Desarrollo de Modelos Pronóstico para la calidad del Aire en la Zona Metropolitana de Guadalajara, Jalisco, Tesis de Licenciatura, ESIQIE-IPN, México (2006).
23. Shamim, M. A., Ghumman A. R., Ghani U.; TForecasting Groundwater Contamination using Artificial Neural Networks, "International Conf on Water Resources & Arid Environment". (2004).
24. Thomas, S. y B. J. Robert; Model for forecasting expressway fine particulate matter and carbon monoxide concentration: Application of Regression and Neural Network Model, Air & Waste Management Association". 57, 480-488 (2007).
25. Volke, T., J. A. Velasco y D. A. de la Rosa; Suelos contaminados por metales y metaloides: muestreo y alternativas para su remediación, Instituto Nacional de Ecología (2005).
26. Wang, M. X. Liu G. D., Wu W. L., Bao Y. H., Liu W. N.; Prediction of agriculture derived groundwater nitrate distribution in North China Plain with GIS-based BPNN, Environment Geology". 50, 637-644 (2006).
27. Yesilnacar, M. I., Erkan S., Naz M. y Bestamin O.; Neural network prediction of nitrate in groundwater of Harran Plain, Turkey, Environmental Geology". (2007).
28. Yetilmezsoy, K. y Demirel S.; Artificial neural networks (ANN) approach for modeling of Pb (II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) Shells, "Journal of Hazardous Materials". 153, 1288 - 1300 (2008).