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Sayed M Bateni

Showing results (1-10 of 20) with videos related to

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Scientific Reports|October 24, 2025
Scour depth estimation using standalone metaheuristic algorithms and their combinations with CatBoostNasrin Eini, Saeid Janizadeh, Sayed M Bateni, et al.
Scientific Data|October 15, 2025
A Comprehensive Water Chemistry Dataset for Iranian RiversErfan Zarei, Roohollah Noori, Changhyun Jun, et al.
Journal of Environmental Management|July 9, 2024
Impact of climate change on future flood susceptibility projections under shared socioeconomic pathway scenarios in South Asia using artificial intelligence algorithmsSaeid Janizadeh, Dongkyun Kim, Changhyun Jun, et al.
Environmental Science and Pollution Research International|October 3, 2024
Machine learning-based modeling of surface water temperature dynamics in arctic lakesHyung Il Kim, Dongkyun Kim, Mohammad Milad Salamattalab, et al.
The Science of the Total Environment|February 11, 2023
Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithmsMostafa Riazi, Khabat Khosravi, Kaka Shahedi, et al.
Environmental Pollution (Barking, Essex : 1987)|May 29, 2024
Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystemsHyung Il Kim, Dongkyun Kim, Mehran Mahdian, et al.
Environmental Science and Pollution Research International|March 4, 2024
Comparative study for coastal aquifer vulnerability assessment using deep learning and metaheuristic algorithmsMojgan Bordbar, Essam Heggy, Changhyun Jun, et al.
Scientific Reports|August 9, 2024
Publisher Correction: Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithmMasoud Karbasi, Mumtaz Ali, Sayed M Bateni, et al.
Environmental Science & Technology|January 16, 2025
Predicting Chlorophyll-<i>a</i> Concentrations in the World's Largest Lakes Using Kolmogorov-Arnold NetworksMohammad Javad Saravani, Roohollah Noori, Changhyun Jun, et al.
Scientific Reports|July 1, 2024
Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithmMasoud Karbasi, Mumtaz Ali, Sayed M Bateni, et al.
Pageof 2

Showing results (1-10 of 20) with videos related to

Sort By:
Pageof 2
Scientific Reports|October 24, 2025
Scour depth estimation using standalone metaheuristic algorithms and their combinations with CatBoostNasrin Eini, Saeid Janizadeh, Sayed M Bateni, et al.
Scientific Data|October 15, 2025
A Comprehensive Water Chemistry Dataset for Iranian RiversErfan Zarei, Roohollah Noori, Changhyun Jun, et al.
Journal of Environmental Management|July 9, 2024
Impact of climate change on future flood susceptibility projections under shared socioeconomic pathway scenarios in South Asia using artificial intelligence algorithmsSaeid Janizadeh, Dongkyun Kim, Changhyun Jun, et al.
Environmental Science and Pollution Research International|October 3, 2024
Machine learning-based modeling of surface water temperature dynamics in arctic lakesHyung Il Kim, Dongkyun Kim, Mohammad Milad Salamattalab, et al.
The Science of the Total Environment|February 11, 2023
Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithmsMostafa Riazi, Khabat Khosravi, Kaka Shahedi, et al.
Environmental Pollution (Barking, Essex : 1987)|May 29, 2024
Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystemsHyung Il Kim, Dongkyun Kim, Mehran Mahdian, et al.
Environmental Science and Pollution Research International|March 4, 2024
Comparative study for coastal aquifer vulnerability assessment using deep learning and metaheuristic algorithmsMojgan Bordbar, Essam Heggy, Changhyun Jun, et al.
Scientific Reports|August 9, 2024
Publisher Correction: Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithmMasoud Karbasi, Mumtaz Ali, Sayed M Bateni, et al.
Environmental Science & Technology|January 16, 2025
Predicting Chlorophyll-<i>a</i> Concentrations in the World's Largest Lakes Using Kolmogorov-Arnold NetworksMohammad Javad Saravani, Roohollah Noori, Changhyun Jun, et al.
Scientific Reports|July 1, 2024
Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithmMasoud Karbasi, Mumtaz Ali, Sayed M Bateni, et al.
Pageof 2