Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Monthly suspended sediment load prediction using artificial intelligence: testing of a new random subspace method
Viet‐Ha Nhu, Khabat Khosravi, James R. Cooper, et al.
Hydrological Sciences Journal (2020) Vol. 65, Iss. 12, pp. 2116-2127
Closed Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

Ensemble machine learning paradigms in hydrology: A review
Mohammad Zounemat‐Kermani, Okke Batelaan, Marzieh Fadaee, et al.
Journal of Hydrology (2021) Vol. 598, pp. 126266-126266
Open Access | Times Cited: 440
Suspended sediment load prediction using sparrow search algorithm-based support vector machine model
Sandeep Samantaray, Abinash Sahoo, Deba Prakash Satapathy, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 26
Artificial intelligence for suspended sediment load prediction: a review
Deepak Gupta, Barenya Bikash Hazarika, M. Berlin, et al.
Environmental Earth Sciences (2021) Vol. 80, Iss. 9
Closed Access | Times Cited: 62
A comparative survey between cascade correlation neural network (CCNN) and feedforward neural network (FFNN) machine learning models for forecasting suspended sediment concentration
Bhupendra Joshi, Vijay Kumar Singh, Dinesh Kumar Vishwakarma, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 9
Prediction of suspended sediment concentration using hybrid SVM-WOA approaches
Sandeep Samantaray, Abinash Sahoo
Geocarto International (2021) Vol. 37, Iss. 19, pp. 5609-5635
Closed Access | Times Cited: 44
Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach
Khabat Khosravi, Ali Golkarian, Assefa M. Melesse, et al.
Journal of Hydrology (2022) Vol. 610, pp. 127963-127963
Closed Access | Times Cited: 30
A newly developed multi-objective evolutionary paradigm for predicting suspended sediment load
Siyamak Doroudi, Ahmad Sharafati
Journal of Hydrology (2024) Vol. 634, pp. 131090-131090
Closed Access | Times Cited: 8
Applying a machine learning-based method for the prediction of suspended sediment concentration in the Red river basin
Son Nguyen, L. Nguyen, Thanh Ngo‐Duc, et al.
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 2, pp. 2675-2692
Closed Access | Times Cited: 6
Suspended sediment load prediction using artificial intelligence techniques: comparison between four state-of-the-art artificial neural network techniques
Khalil Rezaei, Biswajeet Pradhan, Meysam Vadiati, et al.
Arabian Journal of Geosciences (2021) Vol. 14, Iss. 3
Open Access | Times Cited: 31
On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils
Duong Kien Trong, Binh Thai Pham, Fazal E. Jalal, et al.
Materials (2021) Vol. 14, Iss. 21, pp. 6516-6516
Open Access | Times Cited: 31
Combining Radial Basis Function Neural Network Models and Inclusive Multiple Models for Predicting Suspended Sediment Loads
Elham Ghanbari-Adivi, Mohammad Ehteram, Alireza Farrokhi, et al.
Water Resources Management (2022) Vol. 36, Iss. 11, pp. 4313-4342
Closed Access | Times Cited: 20
Developing ensemble models for estimating sediment loads for different times scales
Majid Niazkar, Mohammad Zakwan
Environment Development and Sustainability (2023) Vol. 26, Iss. 6, pp. 15557-15575
Closed Access | Times Cited: 13
Using an interpretable deep learning model for the prediction of riverine suspended sediment load
Zeinab Mohammadi-Raigani, Hamid Gholami, Aliakbar Mohamadifar, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 22, pp. 32480-32493
Closed Access | Times Cited: 4
Climate change as main driver of centennial decline in river sediment transport across the Mediterranean region
Marco Luppichini, Marco Lazzarotti, Mónica Bini
Journal of Hydrology (2024) Vol. 636, pp. 131266-131266
Open Access | Times Cited: 4
Development of machine learning models for estimation of daily evaporation and mean temperature: a case study in New Delhi, India
Jitendra Rajput, Nand Lal Kushwaha, Aman Srivastava, et al.
Water Practice & Technology (2024) Vol. 19, Iss. 7, pp. 2655-2672
Open Access | Times Cited: 4
Drought forecasting using new advanced ensemble-based models of reduced error pruning tree
Mojtaba Shahdad, Behzad Saber
Acta Geophysica (2022) Vol. 70, Iss. 2, pp. 697-712
Closed Access | Times Cited: 19
Estimation of suspended sediment load utilizing a super-optimized deep learning approach informed by the red fox optimization algorithm
Mohammad Mahdi Malekpour, Mohammad Mehdi Ahmadi, Marcello Gugliotta, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 3
Closed Access
Prediction of suspended sediment load in Sungai Semenyih using extreme learning machines and metaheuristic optimization approach
Azlan Saleh, Mohd Asyraf Zulkifley
Journal of Environmental Management (2025) Vol. 380, pp. 124987-124987
Closed Access
Standalone and Hybrid machine learning approaches to predict sediment load in an alluvial channel
Sanjit Kumar, Vishal Deshpande, Mayank Agarwal
Engineering Applications of Artificial Intelligence (2025) Vol. 150, pp. 110578-110578
Closed Access
Landslide Susceptibility Assessment Using Hybrid Method of Best-first Decision Tree and Machine Learning Ensembles
Weipeng Li, Jianguo Wang, Linhai Li, et al.
KSCE Journal of Civil Engineering (2025), pp. 100199-100199
Open Access
Bayesian-optimized recursive machine learning for predicting human-induced changes in suspended sediment transport
Soumya Kundu, Somil Swarnkar, Akshay Agarwal
Environmental Monitoring and Assessment (2025) Vol. 197, Iss. 5
Closed Access
Image-driven hydrological parameter coupled identification of flood plain wetland conservation and restoration sites
Swades Pal, Pankaj Singha
Journal of Environmental Management (2022) Vol. 318, pp. 115602-115602
Closed Access | Times Cited: 16
Comparative Study of Suspended Sediment Load Prediction Models Based on Artificial Intelligence Methods
Cynthia Borkai Boye, Paul Boye, Yao Yevenyo Ziggah
Artificial Intelligence and Applications (2023) Vol. 2, Iss. 2, pp. 141-154
Open Access | Times Cited: 9
Identifying the acute toxicity of contaminated sediments using machine learning models
Min Jeong Ban, Dong Hoon Lee, Sang Wook Shin, et al.
Environmental Pollution (2022) Vol. 312, pp. 120086-120086
Closed Access | Times Cited: 14
Predicting wetland area and water depth in Barind plain of India
Pankaj Singha, Swades Pal
Environmental Science and Pollution Research (2022) Vol. 29, Iss. 47, pp. 70933-70949
Closed Access | Times Cited: 13
Page 1 - Next Page

Scroll to top