S. Emamgholizadeh; Ph.D.
S. Emamgholizadeh; Ph.D.
Associate Professor of Water Engineering,Shahrood University of Technology
Verified email at shahroodut.ac.ir - Homepage
Cited by
Cited by
Prediction the Groundwater Level of Bastam Plain (Iran) by Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS)
S Emamgholizadeh, K Moslemi, G Karami
Water Resources Management 28 (Issue 15 (2014)), Page 5433-54, 2014
Prediction of water quality parameters of Karoon River (Iran) by artificial intelligence-based models
S Emamgholizadeh, H Kashi, I Marofpoor, E Zalaghi
International Journal of Environmental Science and Technology 11 (3), 645-656, 2014
Estimation of soil cation exchange capacity using Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS)
S Emamgolizadeh, SM Bateni, D Shahsavani, T Ashrafi
Journal of Hydrology 529 (Part 3), 1590–1600, 2015
Seed yield prediction of sesame using artificial neural network
S Emamgholizadeh, M Parsaeian, M Baradaran
European Journal of Agronomy 68, 89-96, 2015
Investigation and evaluation of the pressure flushing through storage reservoir
S Emamgholizadeh, M Bina, M Fathi-Moghadam, M Ghomeyshi
ARPN Journal of Engineering and Applied Sciences 1 (4), 7-16, 2006
Prediction of discharge coefficient of triangular labyrinth weirs using Adaptive Neuro Fuzzy Inference System
AH Haghiabi, A Parsaie, S Ememgholizadeh
Alexandria Engineering Journal, 2017
Estimation of soil cation exchange capacity using multiple regression, artificial neural networks, and adaptive neuro-fuzzy inference system models in Golestan Province, Iran
H Ghorbani, H Kashi, N Hafezi Moghadas, S Emamgholizadeh
Communications in Soil Science and Plant Analysis 46 (6), 763-780, 2015
Estimation of soil infiltration and cation exchange capacity based on multiple regression, ANN (RBF, MLP), and ANFIS models
H Kashi, S Emamgholizadeh, H Ghorbani
Communications in soil science and plant analysis 45 (9), 1195-1213, 2014
Prediction of water quality parameters using evolutionary computing-based formulations
M Najafzadeh, A Ghaemi, S Emamgholizadeh
International Journal of Environmental Science and Technology 16 (10), 6377-6396, 2019
Physical modelling of pressure flushing for desilting of non-cohesive sediment
M Fathi-Moghadam, S Emamgholizadeh, M Bina, M Ghomeshi
Journal of hydraulic research 48 (4), 509-514, 2010
Physical and numerical modeling of submerged vegetation roughness in rivers and flood plains
M Fathi-Moghadam, M Kashefipour, N Ebrahimi, S Emamgholizadeh
Journal of Hydrologic Engineering 16 (11), 858-864, 2011
A comparison of artificial intelligence models for the estimation of daily suspended sediment load: a case study on the Telar and Kasilian rivers in Iran
S Emamgholizadeh, RK Demneh
Water Supply 19 (1), 165-178, 2019
Evolution of developing flushing cone during the pressurized flushing in reservoir storage
ME Meshkati, AA Dehghani, G Naser, S Emamgholizadeh, A Mosaedi
World Academy of Science, Engineering and Technology 58, 1107-1111, 2009
Artificial intelligence-based estimation of flushing half-cone geometry
S Emamgholizadeh, SM Bateni, DS Jeng
Engineering Applications of Artificial Intelligence 26 (10), 2551-2558, 2013
Desilting of deposited sediment at the upstream of the Dez reservoir in Iran
S Emamgholizadeh, H Samadi
Journal of Applied Sciences in Environmental Sanitation 3 (1), 25-35, 2008
Predicting water level drawdown and assessment of land subsidence in Damghan aquifer by combining GMS and GEP models
S Parhizkar, K Ajdari, GA Kazemi, S Emamgholizadeh
Geopersia 5 (1), 63-80, 2015
Pressure flushing of cohesive sediment in large dam reservoirs
S Emamgholizadeh, M Fathi-Moghdam
Journal of Hydrologic Engineering 19 (4), 674-681, 2014
Settling properties of cohesive sediments in lakes and reservoirs
M Fathi-Moghadam, A Arman, S Emamgholizadeh, A Alikhani
Journal of waterway, port, coastal, and ocean engineering 137 (4), 204-209, 2011
Estimation of soil dispersivity using soft computing approaches
S Emamgholizadeh, K Bahman, S Bateni, H Ghorbani, I Marofpoor, ...
Neural Computing and Applications 28 (10.1007/s00521-016-2320-x), 207-216, 2017
Estimation of Wind Drift and Evaporation Losses from Sprinkler Irrigation systemS by Different Data‐Driven Methods
E Maroufpoor, H Sanikhani, S Emamgholizadeh, Kişi
Irrigation and Drainage 67 (2), 222-232, 2018
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