‪HEDDAM SALIM, HDR, Full Professor‬

Citado por

	Total	Desde 2020
Citas	5274	4685
Índice h	43	40
Índice i10	109	108

1500

750

375

1125

20142015201620172018201920202021202220232024202529 26 79 71 136 214 389 655 806 1157 1443 222

Acceso público

Ver todo

14 artículos

3 artículos

disponibles

no disponibles

Basado en requisitos de financiación

Coautores

Ozgur KisiDepartment of Civil Engineering, University of Applied Sciences, Lübeck, GermanyDirección de correo verificada de th-luebeck.de
Sungwon KimProfessor, Dept. of Railroad Construction and Safety Engineering, Dongyang UniversityDirección de correo verificada de dyu.ac.kr
Rana Muhammad Adnan IkramResearch Professor, Guangzhou UniversityDirección de correo verificada de gzhu.edu.cn
Mohammad Zounemat-KermaniDepartment of Water Engineering, Shahid Bahonar University of Kerman, Kerman, IranDirección de correo verificada de uk.ac.ir
Lakhdar DjemilihydrauliqueDirección de correo verificada de univ-annaba.dz
Anurag MalikPunjab Agricultural UniversityDirección de correo verificada de pau.edu
Larbi HouichiProfessor, University of Batna 2, AlgeriaDirección de correo verificada de univ-batna2.dz
Meysam AlizamirPhD, Civil engineering departmentDirección de correo verificada de iauh.ac.ir
Behrooz KeshtegarProfessor, University of ZabolDirección de correo verificada de uoz.ac.ir
bermad AbdelMalekENPDirección de correo verificada de g.enp.edu.dz
Binquan LiHohai UniversityDirección de correo verificada de hhu.edu.cn
Hossein BonakdariAssociate ProfessorDirección de correo verificada de fsaa.ulaval.ca
Isa EbtehajResearch Assistant, Université LavalDirección de correo verificada de ulaval.ca
Professor Ravinesh Deo, Highly Cited...Professor in Mathematics and Artificial IntelligenceDirección de correo verificada de usq.edu.au
Andrea PETROSELLITuscia UniversityDirección de correo verificada de unitus.it
Marijana Hadzima-NyarkoFull Professor of Civil Engineering, University J.J.Strossmayer in Osijek, Faculty of CivilDirección de correo verificada de gfos.hr
Emmanuel Karlo NyarkoFaculty of Electrical Engineering, Computer Science and Information Technology, OsijekDirección de correo verificada de etfos.hr
Shun-Peng Zhu (朱顺鹏)Professor, University of Electronic Science and Technology of ChinaDirección de correo verificada de uestc.edu.cn
Sebastiano PiccolroazAssistant Professor, University of Trento, ItalyDirección de correo verificada de unitn.it
ACHOUR BACHIRProfesseur d'Hydraulique, Université de Biskra, AlgérieDirección de correo verificada de univ-biskra.dz

Seguir

HEDDAM SALIM, HDR, Full Professor

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

Dirección de correo verificada de univ-skikda.dz - Página principal

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


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	270	2020
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	266	2022
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	184	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	140	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
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	109	2020
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	108	2021
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	106	2012
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	105	2019
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	104	2020
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
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	100	2021
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	98	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	96	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	91	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	86	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	83	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	80	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	76	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	76	2011

El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.

Artículos 1–20

Citas por año

Citas duplicadas

Citas combinadas

Añadir coautoresCoautores

Seguir

Citado por

Coautores