1- Fischer, H. B., List, E. J., Koh, R. C. Y., Imberger, J., and Brooks, N. H. (1979). Mixing in inland and coastal waters, 1st Ed., Academic,New York.
2- Iwasa, Y., and Aya, S. (1991). “Predicting longitudinal dispersion coefficient in open-channel flows.” Proc. Int. Symp. on Environmental Hydrology, Hong Kong, 505-510.
3- Seo, I.W., and Cheong, T. S. (1998). “Predicting longitudinal dispersion coefficient in natural Streams.” J. of Hydraulics Eng., 124 (1), 25-32.
4- Kashefipour, M. S., and Falconer, R. A. (2002). “Longitudinal dispersion coefficients in natural channels.” Water Res., 36(6), 1596-1608.
5- Tayfur, G., and Singh, V.P. (2005). “Predicting longitudinal dispersion coefficient in natural streams by artificial neural network.” J. of Hydraulic Engineering, 131 (11), 991-1000.
6- Noori, R., Karbassi, A.R., Farokhnia, A., and Dehghani, M. (2009). “Predicting the longitudinal dispersion coefficient using support vector machine and adaptive neuro-fuzzy inference system techniques.” Environmrntal Engineering Science, 26 (10), 1503-1510.
7- Noori, R., Karbassi, A., Mehdizadeh, H., Vesali-Naseh, M. and Sabahi, M. S. (2010). “Development of a framework for predicting the longitudinal dispersion coefficient in natural streams using artificial neural network.” Environmental Progress and Sustainable Energy, DOI: 10.1002/ep.10478.
8- Huber, P.J. (1981). Robust statistics, 1st Ed., John Wiley and Sons Inc.,New York.
9- Deng, Z. Q., Singh, V. P., and Bengtsson, L. (2001). “Longitudinal dispersion coefficient in straight rivers.” J. Hydraul. Eng., 127(11), 919-927.
10- Fischer, H. B. (1975). “Discussion of simple method for predicting dispersion in streams.” J. of Environ Eng Div ASCE, 101, 453-455.
11- Haykin, S. (1999). Neural networks: A comprehensive foundation, 2nd Ed.,Prentice Hall,New Jersey.
12- Maier, H.R., and Dandy, G.C. (2000). “Neural networks for the prediction and forecasting water resources variables: A review of modeling issues and applications.” J. Env. Model. Soft., 15 (23), 101-124.
13- Noori, R., Farokhnia, A., Morid, S., and Riahi Madvar, H. (2008). “Effect of input variables preprocessing in artificial neural network on monthly flow prediction by PCA and wavelet transformation.” J. of Water and Wastewater, 69, 13-22. (In persian)
14- Noori, R., Hoshiyaripour, G.A., Ashrafi, K., and Araabi, B.N. (2009). “Uncertainty analysis of developed ANN and ANFIS models in prediction of carbon monoxide daily concentration.” Atmospheric Environment, 44 (4), 476-482.
15- Noori, R., Khakpour, A., Omidvar, B., and Farokhnia, A. (2010). “Comparison of ANN and principal component analysis-multivariate linear regression models for predicting the river flow based on developed discrepancy ratio statistic.” Expert Systems with Applications, 37 (8), 5856-5862.
16- Noori, R., Karbassi, A.R., and Sabahi, M.S. (2009). “Evaluation of PCA and gamma test techniques on ANN operation for weekly solid waste prediction.” J. of Environmental Management, 91 (3), 767-771.
17- Dennis, J.E., and Schnabel, R.B. (1983). Numerical methods for unconstrained optimization and nonlinear equations, 1st Ed.,Prentice-Hall,New York.
18- Battiti, R., (1992), “First and second order methods for learning: Between steepest descent and Newton’s method.” Neural Computation, 4(2), 141-166.
19- Fletcher, D, and Goss, E. (1993). “Forecasting with neural networks: An application using bankruptcy data.” Inf. Management, 24 (32), 159-167.