بهبود پیش بینی بارش ماهانه با استفاده از مدل تلفیقی بر پایه روش کرنل- تبدیل موجک و تجزیه ی یکپارچه مد تجربی کامل

[1] M.j. Nazemsadat, A.A. Gamgar Haghighi, M. Sharifzadeh, M. Ahmadvand, Adoption of long-term rainfall forecasts ( studied by wheat farmers in Fars Province), Journal of Iranian Agricultural Science and Education, 22 (2006)1-15. [in Persian]

[2] P. Tofani, E. Mosaedi, A. Fakheri Fard, Precipitation forecast using wavelet theory, Water and Soil Journal (Agriculture Sciences and Technology), 25(5) (2011)1217-1226. [in Persian]

[3] H. Sharifan, B. Ghahreman, Estimation of Rain Forecast Using ARIMA Technique in Golestan Province, Journal of Agricultural Sciences and Natural Resources, 14 (2008) 13-14. [in Persian]

[4] M. Gholabi, A. Akhund, Ali, F. Radmanesh, M. Kashifipour , Comparison of Predicting the Jenkins Box Models in Seasonal Modeling (Case Study: Selected Stations in Khuzestan Province), Quarterly Journal of Geographic Research, 29(3) (2012) 61-72. [in Persian]

[5] A. S. Soltani, A. Saberi, M. Gheisouri, Determination of the best time series model for forecasting annual rainfall of selected stations of Western Azerbaijan province, Researches in Geographical Sciences, 17(44) (2017) 87105.

[6] ASCE, Task Committee on Application of Artificial Neural Networks in Hydrology, Artificial Neural Networks in hydrology. I: Preliminary concepts, Hydrological Engineering, ASCE. 5(2) (2000) 115-123.

[7] C. Siviapragasam, S. Liong, Rainfall and runoff forcasting with SSA-SVM approach, Hydroinformation, 3(2001) 141-152.

[8] K. Roushangar, R. Ghasempour, The study of the performance of classical and artificial intelligence methods in the estimation of roughness coefficients in pontoons, Irrigation and Drainage Journal of Iran, 12(4) (2019) 811-822. [in Persian]

[9] O. Kisi, M. Cimen, Precipitation forecasting by using wavelet-support vector machine conjunction model, Engineering Application Artificial Intelligence, 25 (2012) 783–792.

[10] F.S. Marzano, E. Fionda, P. Ciotti, Neural-network approach to ground- based passive microwave estimation of precipitation intensity and extinction,  Hydrology, 328 (2006) 121–131.

[11] Z. Razzaghzadeh, V. Nourani, N. Behfar, The conjunction of feature extraction method with AI-based ensemble statistical downscaling models, Amirkabir Journal of Civil Engineering, DOI: 10.22060/ceej.2018.14986.5806, (2018). [in Persian]

[12] S. Kumar, D. Tripathy, S. Nayak, S. Mohaparta, Prediction of rainfall in India using artificial neural network models, International Journal of intelligent system and applications, 12 (2013) 1-22.

[13] D. Nayak, A. Mahapatra, P. Mishra, A survey on rainfall prediction using artificial neural network, International journal of computer applications, 72(16) (2013) 32-40.

[14] K.M. Lau, H.Y. Weng, Climate signal detection using wavelet transform, How to make time series sing, Bull Am Meteorol Soc, 76 (1995) 2391-2402.

[15] K. Adamowski, A. Prokoph, J. Adamowski, Development of a new method of wavelet aided trend detection and estimation, Hydrology Process, 23(18) (2009) 2686–2696.

[16] C.M. Chou, Complexity analysis of rainfall and runoff time series based on sample entropy in different temporal scales, Stochastic Environmental Research and Risk Assessment, 6 (2011) 1401–1408.

[17] Y. Amirat, M. Benbouzidb, T. Wang, K. Bacha, G. Feld, EEMD-based notch filter for induction machine bearing faults detection, Applied Acoustics, 133 (2018)  202–209.

[18] Z. Wu, N.F. Huang, A study of the characteristics of white noise using the empirical mode decomposition method, Proc RS Lond 460A: 1597–1611, (2004).

[19] C.E. Rasmussen, C.K.I. Williams, Gaussian Processes for Machine Learning. The MIT Press, Cambridge, MA, (2006).

[20] W.C. Dawson, R. Wilby, An artificial neural network approach to rainfall-runoff modelling. Hydrological Sciences Journal, 43(1) (1998) 47-66.

[21] NOAA Earth System Research laboratory, https://www.esrl.noaa.gov/psd/data/climateindices/list/, (2009).