Multi-station artificial intelligence based ensemble modeling of suspended sediment load | Citedby Results | Water Supply | IWA Publishing

Skip to Main Content

Skip Nav Destination

Multi-station artificial intelligence based ensemble modeling of suspended sediment load

Water Supply (2022) 22 (1): 707–733.

This article has been cited by the following articles in journals that are participating in CrossRef Cited-by Linking.

Leveraging explainable machine learning for enhanced management of lake water quality

Sajad Soleymani Hasani
Mauricio E. Arias
Hung Q. Nguyen
Osama M. Tarabih
Zachariah Welch
Qiong Zhang

Journal of Environmental Management (2024) 370: 122890.

Drought index downscaling using AI-based ensemble technique and satellite data

Nazanin Behfar
Elnaz Sharghi
Vahid Nourani
Martijn J. Booij

Theoretical and Applied Climatology (2024) 155 (3): 2379.

Spatiotemporal assessment of groundwater quality and quantity using geostatistical and ensemble artificial intelligence tools

Vahid Nourani
Amirreza Ghaffari
Nazanin Behfar
Ehsan Foroumandi
Ali Zeinali
Chang-Qing Ke
Adarsh Sankaran

Journal of Environmental Management (2024) 355: 120495.

Kernel-Based Versus Tree-Based Data-Driven Models: On Applying Suspended Sediment Load Estimation

Mohammad Taghi Sattari
Halit Apaydin
Adam Milweski

Water (2024) 16 (20): 2973.

Approximation in scour depth around spur dikes using novel hybrid ensemble data-driven model

Balraj Singh
Vijay K. Minocha

Water Science & Technology (2024) 89 (4): 962.

Prediction of pull-out behavior of timber glued-in glass fiber reinforced polymer and steel rods under various environmental conditions based on ANN and GEP models

Mostafa Mohammadzadeh Taleshi
Nima Tajik
Alireza Mahmoudian
Mohammad Yekrangnia

Case Studies in Construction Materials (2024) 20: e02842.

Improving the predictive skills of hydrological models using a combinatorial optimization algorithm and artificial neural networks

Juan F. Farfán
Luis Cea

Modeling Earth Systems and Environment (2023) 9 (1): 1103.

Satellite-based estimation of daily suspended sediment load using hybrid intelligent models

Siyamak Doroudi
Ahmad Sharafati
Seyed Hossein Mohajeri

Hydrological Sciences Journal (2023) 68 (2): 307.

Determining susceptible body parts of construction workers due to occupational injuries using inclusive modelling

Kerim Koc
Ömer Ekmekcioğlu
Asli Pelin Gurgun

Safety Science (2023) 164: 106157.

Multi-Channel Assessment Policies for Energy-Efficient Data Transmission in Wireless Underground Sensor Networks

Rajasoundaran Soundararajan
Prince Mary Stanislaus
Senthil Ganesh Ramasamy
Dharmesh Dhabliya
Vivek Deshpande
Sountharrajan Sehar
Durga Prasad Bavirisetti

Energies (2023) 16 (5): 2285.