1. Rajaee T, Jafari H. Prediction of Water Sodium Absorption Ratio (SAR) using ANN and Wavelet Conjunction Model (Case Study: Rudbar Station of Sefidrud River). Journal pf water and soil. 2016; 26(2.2): 189-205.
2. Banejad H, Kamali M, Amirmoradi K, Olyaie E. Forecasting Some of the Qualitative Parameters of Rivers Using Wavelet Artificial Neural Network Hybrid (W-ANN) Model (Case of study: Jajroud River of Tehran and Gharaso River of Kermanshah). Iran. J. Health & Environ. 2012; 6(3).[Persian]
3. Guang-ming Z, Hong-wei L, Xiang-can J, XU M. Assessment of the water quality and nutrition of the Dongting lake with wavelet neural network. Journal of Hunan University. 2005; 32:91-94.
4. Sengorur B, Dogan E, Koklu R, Samandar A. Dissolved oxygen estimation using artificial neural network for water quality control. Fresenius Environmental Bulletin. 2006; 15:1064–1067.
5. Noorani V, Salehi K. Modeling of rainfall - runoff using fuzzy neural network and adaptive neural networks and fuzzy inference methods compare. Prosceedings of 4th National Congress on Civil Engineering. 2008; Tehran. [Persian]
6. Zhou HC, Peng Y, Liang G-H. The research of monthly discharge predictor-corrector model based on wavelet decomposition. Water Resour Manag. 2008; 22(2):217–227.
7. Najah A, Elshafie A, Karim O, Jaffar O. Prediction of Johor river water quality parameters using artificial neural networks. European Journal of Scientific Research. 2009; 28: 422-35.
8. Sighn KP, Basant A, Malik A, Jain G. Artificial neural network modeling of the river water quality-A case study. Ecological Modelling. 2009; 220: 888–895.
9. Rajaee T. Wavelet and neuro-fuzzy conjunction approach for suspended sediment prediction. Clean-Soil Air Water. 2010; 38(3):275–286. [Persian]
10. Kisi O, Shiri J. Precipitation forecasting using wavelet-genetic programming and wavelet-neuro-fuzzy conjunction models. Water Resour Manag. 2011; 25:3135–3152.
12. Moosavi V, Vafakhah M, Shirmohammadi B, Ranjbar M. Optimization of wavelet-ANFIS and wavelet-ANN hybrid models by Taguchi method for groundwater level forecasting. Arab. J. Sci. Eng. 2013b; DOI 10.1007/s13369-013-0762-3.
14. Yarar A. A hybrid wavelet and neuro-fuzzy model for forecasting the monthly streamflow data. Water Resour Manag. 2014; 28:553–565.
15. Alizadeh MJ, Kavianpour MR. Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean. Marine Pollution Bulletin
. 2015; 98(1-2):171-178.
16. Özger M, Burak Kabataş M. Sediment load prediction by combined fuzzy logic-wavelet method. Journal of Hydroinformatcs. 2015; 17 (6): 930-942.
17. Ravansalar M, Rajaee T, Ergil
M. Prediction of dissolved oxygen in River Calder by noise elimination time series using wavelet transform. Journal of Experimental & Theoretical Artificial Intelligence. 2015; DOI:10.1080/0952813X.2015.1042531.
18. Shafaei M, Kisi O. Lake Level Forecasting Using Wavelet-SVR Wavelet-ANFIS and Wavelet-ARMA Conjunction Models. Water Resources Management
. 2015; DOI:10.1007/s11269-015-1147-z.
19. National Geographical Organization.The Gazetter Of Rivers In The I.R Of Iran, Orumiyeh Lake Watershed. National Geographical Organization Publication. 2016; First Volume, p 67 and 77.
20. Toufani P, Mosaedi A, Fakheri Fard A. Prediction of Precipitation Applying Wavelet Network Model (Case study: Zarringol station, Golestan province, Iran). Journal of Water and Soil. 2011; 25(5): 1217-1226.
21. Jain SK, Das A, Srivastava DK. Application of ANN for reservoir inflow prediction and operation. Journal of Water Resources Planning and Management, ASCE. 1999; 125(5) 263-271.
22. Caudill M. Neural networks primer: Part I. AI Expert. 1987; 2(12): 46-52.
23. Shafaei Y, Farzaneh M, Teshnehlab M. Modeling of producting trip by using Adaptive Neuro-Fuzzy. Issue of Engineering Faculty. 2002; 36(3): 361-170. [Persian]
24. Aalami M.T, Sadeghfam S, Fazelifard M.H, Naghipour L. Data Series Modeling. 2013; Tabriz, University of Tabriz.
25. Barzegar R, Adamowski J, Asghari Moghaddam A. Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran. Stoch Environ Res Risk Assess. 2016; DOI 10.1007/s00477-016-1213-y.