References

Abd, M.K., 2009. Electricity load forecasting based on framelet neural network technique. Am. J. Applied Sci., 6: 970-973.
CrossRef  |  Direct Link  |  

Ajeel, S.A., 2010. A novel carbon steel pipe protection based on radial basis function neural network. Am. J. Applied Sci., 7: 248-251.
CrossRef  |  Direct Link  |  

Baboo, S.S. and I.K. Shereef, 2010. An efficient weather forecasting system using artificial neural network. Int. J. Environ. Sci. Dev., 1: 321-326.
Direct Link  |  

Cheng, C.S., G. Li, Q. Li and H. Auld, 2010. A synoptic weather typing approach to simulate daily rainfall and extremes in Ontario, Canada: Potential for climate change projections. J. Applied Meteorol. Climatol., 49: 845-866.
CrossRef  |  Direct Link  |  

Dastorani, M.T., H. Afkhami, H. Sharifidarani and M. Dastorani, 2010. Application of ANN and ANFIS models on dryland precipitation prediction (case study: Yazd in Central Iran). J. Applied Sci., 10: 2387-2394.
CrossRef  |  Direct Link  |  

Ghods, L. and M. Kalantar, 2010. Long-term peak demand forecasting by using radial basis function neural networks. Iran. J. Electr. Electron. Eng., 6: 175-182.
Direct Link  |  

Goriz, M. and T. Punithori, 2011. A new model for time-series forecasting using radial basis functions. Int. J., 181: 903-916.

Khan, M.S. and P. Coulibaly, 2010. Assessing hydrologic impact of climate change with uncertainty estimates: Back propagation neural network approach. J. Hydrometeorol., 11: 482-495.
CrossRef  |  Direct Link  |  

Luo, L. and L. Zhou, 2010. Application of radial basis function neural network in modeling wastewater sludge recycle system. Commun. Comput. Inform. Sci., 98: 117-122.
CrossRef  |  Direct Link  |  

Moro, Q.I., L. Alonso and C.E. Vivaracho, 1994. Application of neural networks to weather forecasting with local data. Proceedings of the 12th IASTED International Conference on Applied Informatics, May 1994, Annecy, France, pp: 68-70.

Omaima, N.A., 2010. Improving the performance of backpropagation neural network algorithm for image compression/decompression system. J. Comput. Sci., 6: 1347-1354.

Park, J. and I.W. Sandberg, 1991. Universal approximation using radial-basis-function networks. Neural Comput., 3: 246-257.
CrossRef  |  Direct Link  |  

Veisi, H. and M. Jamzad, 2009. A complexity-based approach in image compression using neural networks. Int. J. Sign. Process., 5: 82-92.
Direct Link  |