1. Akbari, Z. and A. Talebi. 2010. Estimation of Suspended Sediment Using Regression Decision Trees Method (Case Study Ilam Dam Basin Science and Technology of Agriculture and Natural Resources Journal, 17: 109-121 (In Persian).
2. Bhattacharya, B., R.K. Price and D.P. Solomatine. 2007. Machine Learning Approach to Modeling Sediment Transport. Journal of Hydraulic Engineering. 133: 440-450. [
DOI:10.1061/(ASCE)0733-9429(2007)133:4(440)]
3. Bauer, P., S. Noatak and R.Winkler. 2007. Fuzzy Mathematical Methods for Soil Survey and Land Evaluation. Journal of Soil science, 40: 477-492.
4. Dastorani, M., Kh. Azimi Fashi, A. Talebi and M. Ekhtesasi. 2012. Suspended Sediment Estimation Using Artificial Neural Network (Case Study: Jamyshan watershed in Kermanshah). Journal of Watershed Management, 3: 61-74 (In Persian).
5. Dehghani, N. and M. Vafakhah. 2013. Comparison of Daily Suspended Sediment Load Estimations by Sediment Rating Curve and Neural Network Models (Case Study: Ghazaghli Station in Golestan Province). Journal of Water and Soil Conservation, 20: 221-230 (In Persian).
6. Falamaki, A., M. Eskandari, A. Baghlani and A. Ahmadi. 2013. Modeling Total Sediment Load in Rivers Using Artificial Neural Networks. Journal of Water and Soil Conservation, 2: 13-26 (In Persian).
7. Kakaei Lafdani, E., A. Pournemat, Roudsari, K. Qaderi and A. Moghaddam Nia. 2013. Predicting the Volume of Suspended Sediments using GMDH and SVM Models Based on Principal Component Analysis. 9th International River Engineering Conference Shahid Chamran University, Ahwaz, pp: 22-24 (In Persian).
8. Heng, S. and T. Suetsugi. 2013. Using Artificial Neural Network to Estimate Sediment Load in Ungauged Catchments of the Tonle Sap River Basin, Cambodia, Journal of Water Resource and Protection, 5: 111-123. [
DOI:10.4236/jwarp.2013.52013]
9. Senthil Kumar, A.R., C.S. Ojha, P. Manish Kumar Goyal, R.D. Singh and P.K. Swamee. 2012. Modeling of Suspended Sediment Concentration at Kasol in India Using ANN, Fuzzy Logic and Decision Tree Algorithms. American Society of Civil Engineers, 17: 394-404.
10. Shabani, M. and N. Shabani. 2012. Estimation of Daily Suspended Sediment Yield Using Artificial Neural Network and Sediment Rating Curve in Kharestan Watershed, Iran, Australian Journal of Basic and Applied Sciences, 6: 157-164 (In Persian).
11. Toloei, S., D. Hossenzadeh, M. Ghorbani, A. Fakhrefard and F. salmasi. 2011. Estimate Temporal and Spatial Suspended load river AJICHAI with Use from Geostatistics and Artificial neural Network. Issue Science Water and Soil, 21: 12-25 (In Persian).
12. Tabatabaei, M., K. Solaimani, M. Habibnejad Roshan and A. Kavian. 2014. Estimation of Daily Suspended Sediment Concentration Using Artificial Neural Networks and Data Clustering by Self Organizing Map (Case Study: Sierra Hydrometry Station- Karaj Dam Watershed). Journal of Watershed Management, 5: 98-116 (In Persian).
13. Yosefi, M. and R. Poorshariaty. 2014. Suspended Sediment Estimation Using Neural Network and Algorithms Assessment (Case Study: Lorestan Province), Watershed Management Journal, 5: 85-67. (In Persian).
14. Yosefi, M., A. Talebi and R. Poorshariaty. 2014. Application of Artificial Intelligence in Water and Soil Sciences. Yazd University publication, Yazd, Iran, 516 pp (In Persian).
15. Zhu, Y.M., X.X. Lu and Y. Zhou. 2007. Suspended Sediment Flux Modeling with Artificial Neural Network: An Example of the Longchunajianj River in the Upper Yangtze Catchment. Geomorphology, 84: 111-125. [
DOI:10.1016/j.geomorph.2006.07.010]