Theo dơi
HEDDAM SALIM, HDR, Full Professor
HEDDAM SALIM, HDR, Full Professor
Faculty of Science, Agronomy Department, Hydraulic Division University 20 Août 1955 SKIKDA 21000
Email được xác minh tại univ-skikda.dz - Trang chủ
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
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
2212020
Groundwater level prediction using machine learning models: A comprehensive review
ZS Hai Tao, Mohammed Majeed Hameed, Haydar Abdulameer Marhoon, Mohammad ...
Neurocomputing 489, 271-308, 2022
1662022
Modelling daily dissolved oxygen concentration using least square support vector machine, multivariate adaptive regression splines and M5 model tree
S Heddam, O Kisi
Journal of Hydrology 559, 499-509, 2018
1662018
Rainfall pattern forecasting using novel hybrid intelligent model based ANFIS-FFA
ZM Yaseen, MI Ghareb, I Ebtehaj, H Bonakdari, R Siddique, S Heddam, ...
Water resources management 32, 105-122, 2018
1362018
ANFIS-based modelling for coagulant dosage in drinking water treatment plant: a case study
S Heddam, A Bermad, N Dechemi
Environmental monitoring and assessment 184, 1953-1971, 2012
1122012
Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors
S Heddam, O Kisi
Environmental Science and Pollution Research 24 (20), 16702-16724, 2017
992017
Modeling daily reference evapotranspiration (ET0) in the north of Algeria using generalized regression neural networks (GRNN) and radial basis function neural …
I Ladlani, L Houichi, L Djemili, S Heddam, K Belouz
Meteorology and Atmospheric Physics 118, 163-178, 2012
982012
Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models
S Zhu, S Heddam, EK Nyarko, M Hadzima-Nyarko, S Piccolroaz, S Wu
Environmental Science and Pollution Research 26, 402-420, 2019
942019
Modeling daily dissolved oxygen concentration using modified response surface method and artificial neural network: a comparative study
B Keshtegar, S Heddam
Neural Computing and Applications 30 (10), 2995-3006, 2018
912018
The implementation of univariable scheme-based air temperature for solar radiation prediction: New development of dynamic evolving neural-fuzzy inference system model
O Kisi, S Heddam, ZM Yaseen
Applied Energy 241, 184-195, 2019
852019
Modelling of daily lake surface water temperature from air temperature: Extremely randomized trees (ERT) versus Air2Water, MARS, M5Tree, RF and MLPNN
S Heddam, M Ptak, S Zhu
Journal of Hydrology 588, 125130, 2020
842020
River water salinity prediction using hybrid machine learning models
AM Melesse, K Khosravi, JP Tiefenbacher, S Heddam, S Kim, A Mosavi, ...
Water 12 (10), 2951, 2020
832020
Short term rainfall-runoff modelling using several machine learning methods and a conceptual event-based model
RM Adnan, A Petroselli, S Heddam, CAG Santos, O Kisi
Stochastic Environmental Research and Risk Assessment 35 (3), 597-616, 2021
792021
Predicting effluent biochemical oxygen demand in a wastewater treatment plant using generalized regression neural network based approach: a comparative study
S Heddam, H Lamda, S Filali
Environmental processes 3, 153-165, 2016
772016
Prediction of dissolved oxygen in urban rivers at the Three Gorges Reservoir, China: extreme learning machines (ELM) versus artificial neural network (ANN)
S Zhu, S Heddam
Water Quality Research Journal, 2019
752019
Applications of radial-basis function and generalized regression neural networks for modeling of coagulant dosage in a drinking water-treatment plant: comparative study
S Heddam, A Bermad, N Dechemi
Journal of Environmental Engineering 137 (12), 1209-1214, 2011
692011
Estimating reference evapotranspiration using hybrid adaptive fuzzy inferencing coupled with heuristic algorithms
RM Adnan, RR Mostafa, ARMT Islam, O Kisi, A Kuriqi, S Heddam
Computers and Electronics in Agriculture 191, 106541, 2021
682021
Extreme learning machine-based prediction of daily water temperature for rivers
S Zhu, S Heddam, S Wu, J Dai, B Jia
Environmental Earth Sciences 78, 1-17, 2019
662019
Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island …
S Heddam
Environmental Science and Pollution Research 21 (15), 9212-9227, 2014
652014
Modeling hourly dissolved oxygen concentration (DO) using two different adaptive neuro-fuzzy inference systems (ANFIS): a comparative study
S Heddam
Environmental Monitoring and Assessment 186 (1), 597-619, 2014
652014
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