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Changhyun Jun

Showing results (11-20 of 26) with videos related to

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BMC Public Health|July 3, 2025
Associations among green spaces, ambient temperature, air pollution, and body mass index: a nationwide study in South Korea from 2008 to 2021Yujin Song, Hoyoung Cha, Jongjin Baik, 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.
Scientific Reports|November 17, 2022
Prediction of monthly dry days with machine learning algorithms: a case study in Northern BangladeshShabbir Ahmed Osmani, Jong-Suk Kim, Changhyun Jun, 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.
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.
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|March 18, 2022
Uncertainty quantification of granular computing-neural network model for prediction of pollutant longitudinal dispersion coefficient in aquatic streamsBehzad Ghiasi, Roohollah Noori, Hossein Sheikhian, et al.
The Science of the Total Environment|February 7, 2025
Pivotal role of snow depth, local atmospheric conditions, and large-scale climate signals on ice thinning in Finnish lakesDanial Naderian, Roohollah Noori, Sayed M Bateni, et al.
Heliyon|December 6, 2024
Daily river flow simulation using ensemble disjoint aggregating M5-Prime modelKhabat Khosravi, Nasrin Attar, Sayed M Bateni, et al.
Pageof 3

Showing results (11-20 of 26) with videos related to

Sort By:
Pageof 3
BMC Public Health|July 3, 2025
Associations among green spaces, ambient temperature, air pollution, and body mass index: a nationwide study in South Korea from 2008 to 2021Yujin Song, Hoyoung Cha, Jongjin Baik, 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.
Scientific Reports|November 17, 2022
Prediction of monthly dry days with machine learning algorithms: a case study in Northern BangladeshShabbir Ahmed Osmani, Jong-Suk Kim, Changhyun Jun, 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.
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.
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|March 18, 2022
Uncertainty quantification of granular computing-neural network model for prediction of pollutant longitudinal dispersion coefficient in aquatic streamsBehzad Ghiasi, Roohollah Noori, Hossein Sheikhian, et al.
The Science of the Total Environment|February 7, 2025
Pivotal role of snow depth, local atmospheric conditions, and large-scale climate signals on ice thinning in Finnish lakesDanial Naderian, Roohollah Noori, Sayed M Bateni, et al.
Heliyon|December 6, 2024
Daily river flow simulation using ensemble disjoint aggregating M5-Prime modelKhabat Khosravi, Nasrin Attar, Sayed M Bateni, et al.
Pageof 3