Theo dơi
Mohammad Zounemat-Kermani
Mohammad Zounemat-Kermani
Department of Water Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Email được xác minh tại - Trang chủ
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Ensemble machine learning paradigms in hydrology: A review
M Zounemat-Kermani, O Batelaan, M Fadaee, R Hinkelmann
Journal of Hydrology 598, 126266, 2021
Daily suspended sediment concentration simulation using ANN and neuro-fuzzy models
T Rajaee, SA Mirbagheri, M Zounemat-Kermani, V Nourani
Science of the total environment 407 (17), 4916-4927, 2009
Solar radiation prediction using different techniques: model evaluation and comparison
L Wang, O Kisi, M Zounemat-Kermani, GA Salazar, Z Zhu, W Gong
Renewable and Sustainable Energy Reviews 61, 384-397, 2016
Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs
RM Adnan, Z Liang, S Heddam, M Zounemat-Kermani, O Kisi, B Li
Journal of Hydrology 586, 124371, 2020
Using adaptive neuro-fuzzy inference system for hydrological time series prediction
M Zounemat-Kermani, M Teshnehlab
Applied soft computing 8 (2), 928-936, 2008
Groundwater level prediction using machine learning models: A comprehensive review
H Tao, MM Hameed, HA Marhoon, M Zounemat-Kermani, S Heddam, ...
Neurocomputing 489, 271-308, 2022
River suspended sediment load prediction: application of ANN and wavelet conjunction model
T Rajaee, V Nourani, M Zounemat-Kermani, O Kisi
Journal of Hydrologic Engineering 16 (8), 613-627, 2011
Daily streamflow prediction using optimally pruned extreme learning machine
RM Adnan, Z Liang, S Trajkovic, M Zounemat-Kermani, B Li, O Kisi
Journal of Hydrology 577, 123981, 2019
Estimation of current-induced scour depth around pile groups using neural network and adaptive neuro-fuzzy inference system
M Zounemat-Kermani, AA Beheshti, B Ataie-Ashtiani, SR Sabbagh-Yazdi
Applied Soft Computing 9 (2), 746-755, 2009
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
RM Adnan, RR Mostafa, O Kisi, ZM Yaseen, S Shahid, ...
Knowledge-Based Systems 230, 107379, 2021
Evaluation of data driven models for river suspended sediment concentration modeling
M Zounemat-Kermani, Ö Kişi, J Adamowski, A Ramezani-Charmahineh
Journal of Hydrology 535, 457-472, 2016
Long-term monthly evapotranspiration modeling by several data-driven methods without climatic data
O Kisi, H Sanikhani, M Zounemat-Kermani, F Niazi
Computers and Electronics in Agriculture 115, 66-77, 2015
Pan evaporation modeling using six different heuristic computing methods in different climates of China
L Wang, O Kisi, M Zounemat-Kermani, H Li
Journal of Hydrology 544, 407-427, 2017
A comparative study of several machine learning based non-linear regression methods in estimating solar radiation: Case studies of the USA and Turkey regions
M Alizamir, S Kim, O Kisi, M Zounemat-Kermani
Energy 197, 117239, 2020
Modeling soil temperatures at different depths by using three different neural computing techniques
O Kisi, M Tombul, MZ Kermani
Theoretical and applied climatology 121, 377-387, 2015
Neurocomputing in surface water hydrology and hydraulics: A review of two decades retrospective, current status and future prospects
M Zounemat-Kermani, E Matta, A Cominola, X Xia, Q Zhang, Q Liang, ...
Journal of Hydrology 588, 125085, 2020
Drought forecasting using novel heuristic methods in a semi-arid environment
O Kisi, AD Gorgij, M Zounemat-Kermani, A Mahdavi-Meymand, S Kim
Journal of Hydrology 578, 124053, 2019
Performance of radial basis and LM-feed forward artificial neural networks for predicting daily watershed runoff
M Zounemat-Kermani, O Kisi, T Rajaee
Applied Soft Computing 13 (12), 4633-4644, 2013
Prediction of solar radiation in China using different adaptive neuro‐fuzzy methods and M5 model tree
L Wang, O Kisi, M Zounemat‐Kermani, Z Zhu, W Gong, Z Niu, H Liu, Z Liu
International Journal of Climatology 37 (3), 1141-1155, 2017
Daily pan evaporation modeling using chi-squared automatic interaction detector, neural networks, classification and regression tree
O Kisi, O Genc, S Dinc, M Zounemat-Kermani
Computers and Electronics in Agriculture 122, 112-117, 2016
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