Genetic Algorithm Driven ANN Model for Runoff Estimation
Tóm tắt
Từ khóa
Tài liệu tham khảo
Beven, J.K. (2001). Rainfall-Runoff Modelling – The Primer, John Wiley & Sons Ltd., Chichester, 2001.
Wilby, R.L., Abrahart, R.J., and Dawson, C.W., 2003. Detection of conceptual model rainfall runoff processes inside an artificial neural network. Hydrologic Sciences Journal. 48(2), p. 163-181.
Ashu Jain, Sudheer, K.P., Sanaga Srinivasulu, 2004. Identification of physical processes inherent in artificial neural network rainfall runoff models. Hydrological Processes, 2004, Vol. 18, No. 3, p. 571-581.
Sudheer, K.P., and Jain, A. 2004. Explaining the internal behavior of artificial neural network river flow models. Hydrologic Processes, 118(4), p. 833-844.
Jain A. and Indurthy, S.K.V.P., 2003. Comparative Analysis of Event based Rainfall-Runoff Modeling Techniques- Deterministic, statistical and Artificial Neural Networks. Journal of Hydrologic Engineering. ASCE, 8(2), p. 1-6.
De Vos N. J. and Rientjes T. H. M., 2005. Constraints of artificial neural networks for rainfall runoff modeling trade-offs in hydrological state representation and model evaluation. Hydrology and Earth System Sciences, 9, p. 111-126,.
May, R.J., Maier, H.R. & Dandy, G.C., 2009b. Development of artificial neural networks for water quality modelling and analysis, in G. Hanrahan (ed.), Modelling of Pollutants in Complex Environmental Systems, Vol. 1, ILM Publications, London, UK, p. 27-62.
Modaress R., 2009. Multi-criteria validation of artificial neural network modelling, Hydrology and Earth System Sciences, 13, p. 411-421.
Jihoon Yang, Vasant G. Honavar, 1998. Feature Subset Selection Using a Genetic Algorithm. Journal IEEE Intelligent Systems, Volume 13 Issue 2.
Sexton R S, Dorsey R E, Johnson J D, 1998. Toward global optimization of neural networks: A comparison of the genetic algorithm and back propagation. Decision Support System, 22, p. 171-185.
Osman Ahmed, Mohd Nord, Suziah Sulaiman, Wan Fatimah, 2009. Study of Genetic Algorithm to fully automate the Design and Training of Artificial Neural Network. International Journal of Computer Science and Network Security, VOL.9 No.1.
H. Paul S., G. Ben S., T. Thomas G., W. Robert S., 2004. Use of genetic algorithms for neural networks to predict community-acquired pneumonia. Artificial Intelligence in Medicine, Vol. 30, Issue 1, p.71-84.
D. Shanti, G. Sahoo, N. Saravanan, 2009. Evolving Connection Weights of ANN using GA with application to the Prediction of Stroke Disease. International Journal of Soft Computing 4(2), p. 95-102, Medwell Publishing.
Asha Gowda, Karegowda, A.S. Manjunath, M.A. Jayaram., 2011. Application of Genetic Algorithm optimized Neural Network connection weights for Medical Diagnosis of PIMA Indians Diabetes. International Journal on Soft Computing (IJSC), Vol.2, No.2, p. 15-23.
J. E. Baker, 1987. Reducing bias and inefficiency in the selection algorithm. Proceedings International Conference on Genetic Algorithms Appl., p. 14-21.
G. Sywerda, 1989. Uniform crossover in genetic algorithm. Proceedings International Conference on Genetic Algorithms, p. 2-9.
R. S. Sexton, R.E. Dorsey, and J. D. Johnson. 1999. Optimization of neural networks: A comparative analysis of the genetic algorithm and simulated annealing. European Journal of Operation Research, Vol. 114, no. 3, p. 589-601.
R. S. Sexton, B. Alidaee, R.E. Dorsey, and J. D. Johnson, 1998. Global optimization for artificial neural networks: A taboo search application. European Journal of Operation Research, vol. 106, no. 2/3, p. 570-584.