Suspended sediment load prediction of river systems: GEP approach

H. Md. Azamathulla; Yong Chong Cuan; Aminuddin Ab. Ghani; Chun Kiat Chang

doi:10.1007/s12517-012-0608-4

Suspended sediment load prediction of river systems: GEP approach

Arabian Journal of Geosciences ◽

10.1007/s12517-012-0608-4 ◽

2012 ◽

Vol 6 (9) ◽

pp. 3469-3480 ◽

Cited By ~ 16

Author(s):

H. Md. Azamathulla ◽

Yong Chong Cuan ◽

Aminuddin Ab. Ghani ◽

Chun Kiat Chang

Keyword(s):

Suspended Sediment ◽

Sediment Load ◽

Suspended Sediment Load ◽

Load Prediction ◽

River Systems

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Suspended sediment load prediction of river systems: An artificial neural network approach

Agricultural Water Management ◽

10.1016/j.agwat.2010.12.012 ◽

2011 ◽

Vol 98 (5) ◽

pp. 855-866 ◽

Cited By ~ 134

Author(s):

A.M. Melesse ◽

S. Ahmad ◽

M.E. McClain ◽

X. Wang ◽

Y.H. Lim

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Suspended Sediment ◽

Sediment Load ◽

Suspended Sediment Load ◽

Network Approach ◽

Load Prediction ◽

River Systems ◽

Neural Network Approach ◽

Artificial Neural Network Approach

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A comparison of various machine learning approaches performance for prediction suspended sediment load of river systems: a case study in Malaysia

Earth Science Informatics ◽

10.1007/s12145-021-00689-0 ◽

2021 ◽

Author(s):

Marwah Sattar Hanoon ◽

Alharazi Abdulhadi Abdullatif B ◽

Ali Najah Ahmed ◽

Arif Razzaq ◽

Ahmed H. Birima ◽

...

Keyword(s):

Machine Learning ◽

Suspended Sediment ◽

Sediment Load ◽

Learning Approaches ◽

Suspended Sediment Load ◽

River Systems

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A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States

Environmental Monitoring and Assessment ◽

10.1007/s10661-015-4381-1 ◽

2015 ◽

Vol 187 (4) ◽

Cited By ~ 109

Author(s):

Ehsan Olyaie ◽

Hossein Banejad ◽

Kwok-Wing Chau ◽

Assefa M. Melesse

Keyword(s):

Artificial Intelligence ◽

United States ◽

Suspended Sediment ◽

Sediment Load ◽

Suspended Sediment Load ◽

River Systems

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Analyzing the uncertainty of suspended sediment load prediction using sequential data assimilation

Journal of Hydrology ◽

10.1016/j.jhydrol.2012.08.049 ◽

2012 ◽

Vol 468-469 ◽

pp. 268-282 ◽

Cited By ~ 47

Author(s):

Marc Leisenring ◽

Hamid Moradkhani

Keyword(s):

Data Assimilation ◽

Suspended Sediment ◽

Sediment Load ◽

Sequential Data ◽

Suspended Sediment Load ◽

Load Prediction ◽

Sequential Data Assimilation

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A Comparative Analysis of Artificial Neural Network and Support Vector Regression for River Suspended Sediment Load Prediction

First International Conference on Sustainable Technologies for Computational Intelligence - Advances in Intelligent Systems and Computing ◽

10.1007/978-981-15-0029-9_27 ◽

2019 ◽

pp. 339-349 ◽

Cited By ~ 2

Author(s):

Barenya Bikash Hazarika ◽

Deepak Gupta ◽

Ashu ◽

Mohanadhas Berlin

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Comparative Analysis ◽

Support Vector Regression ◽

Suspended Sediment ◽

Sediment Load ◽

Support Vector ◽

Suspended Sediment Load ◽

Load Prediction ◽

Artificial Neural

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Investigating a Suitable Empirical Model and Performing Regional Analysis for the Suspended Sediment Load Prediction in Major Rivers of the Aegean Region, Turkey

Water Resources Management ◽

10.1007/s11269-016-1357-z ◽

2016 ◽

Vol 31 (3) ◽

pp. 739-764 ◽

Cited By ~ 4

Author(s):

Asli Ulke ◽

Gokmen Tayfur ◽

Sevinc Ozkul

Keyword(s):

Suspended Sediment ◽

Empirical Model ◽

Sediment Load ◽

Regional Analysis ◽

Suspended Sediment Load ◽

Load Prediction ◽

Aegean Region

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Application of newly developed ensemble machine learning models for daily suspended sediment load prediction and related uncertainty analysis

Hydrological Sciences Journal ◽

10.1080/02626667.2020.1786571 ◽

2020 ◽

Vol 65 (12) ◽

pp. 2022-2042 ◽

Cited By ~ 2

Author(s):

Ahmad Sharafati ◽

Seyed Babak Haji Seyed Asadollah ◽

Davide Motta ◽

Zaher Mundher Yaseen

Keyword(s):

Machine Learning ◽

Uncertainty Analysis ◽

Suspended Sediment ◽

Sediment Load ◽

Suspended Sediment Load ◽

Learning Models ◽

Load Prediction ◽

Ensemble Machine Learning ◽

Machine Learning Models

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Erratum to: A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States

Environmental Monitoring and Assessment ◽

10.1007/s10661-015-4526-2 ◽

2015 ◽

Vol 187 (5) ◽

Cited By ~ 1

Author(s):

Ehsan Olyaie ◽

Hossein Banejad ◽

Kwok-Wing Chau ◽

Assefa M. Melesse

Keyword(s):

Artificial Intelligence ◽

United States ◽

Suspended Sediment ◽

Sediment Load ◽

Suspended Sediment Load ◽

River Systems

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Suspended sediment load prediction based on soft computing models and Black Widow Optimization Algorithm using an enhanced gamma test

Environmental Science and Pollution Research ◽

10.1007/s11356-021-14065-4 ◽

2021 ◽

Author(s):

Fatemeh Panahi ◽

Mohammad Ehteram ◽

Mohammad Emami

Keyword(s):

Suspended Sediment ◽

Soft Computing ◽

Optimization Algorithm ◽

Sediment Load ◽

Suspended Sediment Load ◽

Gamma Test ◽

Load Prediction ◽

Black Widow ◽

Computing Models

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Suspended sediment load prediction using artificial intelligence techniques: comparison between four state-of-the-art artificial neural network techniques

Arabian Journal of Geosciences ◽

10.1007/s12517-020-06408-1 ◽

2021 ◽

Vol 14 (3) ◽

Author(s):

Khalil Rezaei ◽

Biswajeet Pradhan ◽

Meysam Vadiati ◽

Ata Allah Nadiri

Keyword(s):

Neural Network ◽

Artificial Intelligence ◽

Artificial Neural Network ◽

Suspended Sediment ◽

Sediment Load ◽

State Of The Art ◽

Suspended Sediment Load ◽

Load Prediction ◽

Artificial Intelligence Techniques ◽

Artificial Neural

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