‪HEDDAM SALIM, HDR, Full Professor‬

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Ozgur KisiDepartment of Civil Engineering, University of Applied Sciences, Lübeck, GermanyVerifisert e-postadresse på th-luebeck.de
Sungwon KimProfessor, Dept. of Railroad Construction and Safety Engineering, Dongyang UniversityVerifisert e-postadresse på dyu.ac.kr
Rana Muhammad Adnan IkramResearch Professor, Guangzhou UniversityVerifisert e-postadresse på gzhu.edu.cn
Mohammad Zounemat-KermaniDepartment of Water Engineering, Shahid Bahonar University of Kerman, Kerman, IranVerifisert e-postadresse på uk.ac.ir
Lakhdar DjemilihydrauliqueVerifisert e-postadresse på univ-annaba.dz
Larbi HouichiProfessor, University of Batna 2, AlgeriaVerifisert e-postadresse på univ-batna2.dz
Anurag MalikPunjab Agricultural UniversityVerifisert e-postadresse på pau.edu
Meysam AlizamirPhD, Civil engineering departmentVerifisert e-postadresse på iauh.ac.ir
Behrooz KeshtegarProfessor, University of ZabolVerifisert e-postadresse på uoz.ac.ir
Professor Ravinesh Deo, Highly Cited...Professor in Mathematics and Artificial IntelligenceVerifisert e-postadresse på usq.edu.au
bermad AbdelMalekENPVerifisert e-postadresse på g.enp.edu.dz
Binquan LiHohai UniversityVerifisert e-postadresse på hhu.edu.cn
Hossein BonakdariAssociate ProfessorVerifisert e-postadresse på fsaa.ulaval.ca
Isa EbtehajResearch Assistant, Université LavalVerifisert e-postadresse på ulaval.ca
Andrea PETROSELLITuscia UniversityVerifisert e-postadresse på unitus.it
Marijana Hadzima-NyarkoFull Professor of Civil Engineering, University J.J.Strossmayer in Osijek, Faculty of CivilVerifisert e-postadresse på gfos.hr
Emmanuel Karlo NyarkoFaculty of Electrical Engineering, Computer Science and Information Technology, OsijekVerifisert e-postadresse på etfos.hr
Shun-Peng Zhu (朱顺鹏)Professor, University of Electronic Science and Technology of ChinaVerifisert e-postadresse på uestc.edu.cn
Sebastiano PiccolroazAssistant Professor, University of Trento, ItalyVerifisert e-postadresse på unitn.it
ACHOUR BACHIRProfesseur d'Hydraulique, Université de Biskra, AlgérieVerifisert e-postadresse på univ-biskra.dz

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HEDDAM SALIM, HDR, Full Professor

Faculty of Science, Agronomy Department, Hydraulic Division University 20 Août 1955 SKIKDA 21000

Verifisert e-postadresse på univ-skikda.dz - Startside

Artificial Neural Network ANN Multi-Layer Perceptron Neural Network MLPNN Generalized Regression Neural Networks GRNN Radial


Tittel Sorter etter sitater Sorter etter år Sorter etter tittel	Sitert av Sitert av	År
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	269	2022
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	269	2020
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	183	2018
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	141	2018
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	123	2012
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	109	2021
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	108	2020
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	107	2019
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	105	2021
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	105	2020
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	105	2012
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	104	2017
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	99	2018
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	98	2019
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	92	2019
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	89	2016
Application of Water Quality Indices, Machine Learning Approaches, and GIS to Identify Groundwater Quality for Irrigation Purposes: A Case Study of Sahara Aquifer, Doucen Plain … H Gaagai, A., Aouissi, H. A., Bencedira, S., Hinge, G., Athamena, A., Heddam ... Water 15 (2), 289, 2023	84	2023
Comparison of different methodologies for rainfall–runoff modeling: machine learning vs conceptual approach RM Adnan, A Petroselli, S Heddam, CAG Santos, O Kisi Natural Hazards 105, 2987-3011, 2021	78	2021
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	78	2019
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	77	2011

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