Adnan RM, Yaseen ZM, Heddam S, Shahid S, Sadeghi-Niaraki A and Kisi O, 2022. Predictability
performance enhancement for suspended sediment in rivers: Inspection of newly developed hybrid
adaptive neuro-fuzzy system model. International Journal of Sediment Research 37(10): 383–398.
https://doi.org/10.1016/j.ijsrc.2021.10.001
Alp M and Cigizoglu HK, 2007. Suspended sediment load simulation by two artificial neural
network methods using hydrometeorological data. Environmental Modelling and Software 22: 2-13.
Aytek A and Kisi O, 2007. A genetic programming approach to suspended sediment modeling. Journal of
Hydrology 351: 288-298.
Biranvand N, Sepahvand A and Haqizadeh A, 2022. Modeling of suspended sediment using machine
learning algorithms in periods of low and high water (Case study: Kashkan watershed). Soil and Water
Modeling and Management (3)2: DOI: 10.22098/mmws.2022.11262.1115.(In Persian with English
Abstract).
Chen XY and Chau KW, 2016. A Hybrid Double Feedforward Neural Network for Suspended Sediment
Load Estimation, Water Resource Management. 30(7): 2179-2194. https://doi.org/10.1007/s11269-016-
1281-2
Cigizoglu HK and Kisi O, 2006. Methods to improve the neural network performance in suspended sediment
estimation. Journal of Hydrology 317: 221-238.
Eivani1 Z, Ahmadi MM and Qaderi K, 2016. Estimation of suspended sediment load concentration in river
system using Group Method of Data Handling (GMDH). Journal of Watershed Management Research
7(13):218-229. (In Persian with English Abstract).
Hesavi M and Shafaee-Bajestan M, 2010. Estimate of Sediment Bed Load in Karoon River Ahwaz Station.
8th International River Engineering Conference, Date 26 June 2010, Ahwaz, Iran. (In Persian with
English Abstract).
Ivakhnenko AG, 1968. The Group Method of Data Handling-a Rival of the Method of Stochastic
Approximation, Soviet Automatic Control c/c of Avtomatika 1: 43-55.
Jie LC and Yu ST, 2011. Suspended sediment load estimate using support vector machines in Kaoping River
basin. International Conference on Consumer Electronics, Communications and Networks (CECNet).
16-18 April .doi: 10.1109/CECNET.2011.5769267
Keshtegar B, Piri J, Hussan WU, Ikram K, Yaseen M, Kisi O, Adnan RM, Adnan M and Waseem M, 2023.
Prediction of sediment yields using a Data-Driven Radial M5 Tree Model. Journal of Water, 15: 1437.
https://doi.org/10.3390/w15071437
Kisi O and Shiri J, 2012. River Suspended sediment estimation by climate variables implication:
Comparative study among soft computing techniques. Computer and Geosciences 43: 73-82.
Kisi O, Ozkan C and Bahriye A, 2012. Modeling discharge-sediment relationship using neural networks with
Artificial Bee Colony Algorithm. Journal of Hydrology: 94-103.
Mehrizi Haeri AA, 2012. Data mining: concepts, methods and applications. Master's thesis in economic and
social statistics, Faculty of Economics, Allameh Tabatabai University. (In Persian with English
Abstract).
222مرادی نژادنشریه دانش آب و خاک / جلد34شماره2/ سال1403
Moradi-Nejad A, Davoudmaqami D and Moradi M, 2018. Investigating the efficiency of methods for
estimating the suspended sediment load of Qarachai river. Environment and Water Engineering (4)5:
https://doi.org/10.22034/jewe.2020.211925.1341.(In Persian with English Abstract).
Moradi-Nejad A, Khosrobigi S, Akbari M and Hosseini SA, 2023. Evaluation of soft calculation methods in
estimation of river suspended sediment (Hassanabad station of Tirah River). Soil and Water Modeling
and Management. https://doi.10.22098/mmws.2023.12620.1258. (In Persian with English Abstract).
Nikpour MR and Sani Khani H, 2016. Modeling of river suspended sediments using soft calculations
(Darah-Rood River). Irrigation and Water Engineer's Scientific and Research Quarterly. 8(30):29-44.
https://civilica.com/doc/888603. (In Persian with English Abstract).
Qobadian R and Shokri H, 2018. Numerical investigation of factors affecting the distribution of unbalanced
sediment concentration in natural rivers (Case study: Qarasu River, Kermanshah). Journal of Water and
Soil 2(34): 241-253. DOI: 10.22067/jsw.v34i2.7632. (In Persian with English Abstract).
Safavi H, 1390 Engineering Hydrology, Arkan Danesh Publications, 3rd edition, Isfahan. 699P.
Satari MT, Rezazadeh Jodi A, Safdari F and Kahramanzadeh F, 2016. Performance evaluation of M5 tree
model and support vector regression methods in river suspended sediment modeling. Protection of
Water and Soil Resources 6(1):109-124. https://civilica.com/doc/1297623. (In Persian with English
Abstract).
Sheikh Alipour Z, Hasanpour F and Bigi M, 2014. Comparison of artificial intelligence methods in
estimating suspended sediment load (Case study: Sistan River). Water and Soil Conservation Research
7(2): 41-60. (In Persian with English abstract).
Zakaria N, Azamathulla HMD, Chang CHK and Ghani AAB, 2010. Gene expression programming for total
bed material load estimation-a case study. Science of the Total Environment, 408: 5078-5085.
Zhou Y, Lu XX, Huang Y and Zhu YM, 2007. Suspended sediment flux modeling with artificial neural
network: An example of the Longchuanjiang River in the upper Yangtze catchment, China.
Geomorphology 84: 111-125.
)