Changhyun Jun

Spatial wildfire risk assessment for Oahu, Hawaii, using swarm-intelligence-optimized CatBoost and the analytic network process

Helaleh Khoshkam, Saeid Janizadeh, Sayed M. Bateni, Dongkyun Kim et autres

us, Afrique du Sud, kr (code pays fourni par la source)

Unraveling the Effects of Univariate and Multivariate Signal Decomposition Techniques on Daily Reference Evapotranspiration Forecasting

Saba Sadeghlou Kivi, Jinwook Lee, Sayed M. Bateni, Jonathan Deenik et autres

us, Afrique du Sud, kr, ca (code pays fourni par la source)

Scour depth prediction at debris-affected bridge piers using interpretable hybrid machine learning models

Nasrin Eini, Sayed M. Bateni, Changhyun Jun

us, Afrique du Sud, jp (code pays fourni par la source)

An integrated data decomposition and feature selection–based hybrid machine learning framework for enhanced hourly wastewater inflow forecasting at a wastewater treatment plant in Oahu, Hawaii

Jinwook Lee, Sayed M. Bateni, Dongkyun Kim, Changhyun Jun et autres

Study region The Sand Island Wastewater Treatment Plant (WWTP), the primary wastewater management facility on Oahu, Hawaii. Study focus Wastewater inflow (WI) is a critical variable for efficient WWTP management. This study developed a hybrid framework for hourly WI forecasting at lead …

kr, us, Afrique du Sud (code pays fourni par la source)

Evaluating climate driver impacts on precipitation extremes through a bootstrapping-based statistical framework in Bangladesh

Shabbir Ahmed Osmani, Changhyun Jun, Jongjin Baik, Jong-Suk Kim et autres

bd, kr, cn (code pays fourni par la source)

Vegetation Density and Emotional Resilience: The Role of Greenness in Reducing Negative Affect in South Korea

Yookyung Lee, Changhyun Jun, Hyochan Kim, Seungwoo Han et autres

kr (code pays fourni par la source)

Enhancing Flood Mapping Precision through C-band PolSAR Decompositions and Feature-Optimized Deep Learning: dataset

Soohyun Kim, Jinwook Lee, Saeid Janizadeh, Sayed M. Bateni et autres

This repository provides the dataset and supporting materials for the study entitled “Enhancing Flood Mapping Precision through C-band PolSAR Decompositions and Feature-Optimized Deep Learning." Due to licensing restrictions associated with the RADARSAT-2 data purchased through the Earth Observation Data Management System (EODMS) …

us, kr (code pays fourni par la source)

Enhancing Flood Mapping Precision through C-band PolSAR Decompositions and Feature-Optimized Deep Learning: dataset

Soohyun Kim, Jinwook Lee, Saeid Janizadeh, Sayed M. Bateni et autres

This repository provides the dataset and supporting materials for the study entitled “Enhancing Flood Mapping Precision through C-band PolSAR Decompositions and Feature-Optimized Deep Learning." Due to licensing restrictions associated with the RADARSAT-2 data purchased through the Earth Observation Data Management System (EODMS) …

us, kr (code pays fourni par la source)

Estimation of the microbial biomass carbon of soil using a hybrid multilayer perceptron-hunger games search algorithm

Samad Emamgholizadeh, Changhyun Jun, Sayed M. Bateni, Mohammad Reza S. Nobariyan et autres

ir, kr, us, Afrique du Sud, tw (code pays fourni par la source)

Forecasting daily reference evapotranspiration under different hydrological conditions using a hybrid wavelet–Bayesian optimization–Gaussian process regression model

Helaleh Khoshkam, Mohammad Valipour, Sayed Mohammadreza Bateni, Changhyun Jun et autres

• W-BO-GPR outperformed the GPR, BO-GPR, and W-GPR models. • Using daily solar radiation, mean air temperature, and relative humidity in addition to reference evapotranspiration ( ET o ) yielded more accurate results. • The best performance of the models was achieved …

us, kr, ir, cn (code pays fourni par la source)

A data-driven approach for rail temperature estimation from air temperature, solar irradiation, and land surface temperature

Minseo Cho, Kihong Park, Seoyeong Ku, Changhyun Jun et autres

• Rail temperature was estimated using multivariate regression and machine learning. • A scenario-based framework was proposed for practical rail temperature estimation. • Linear regression achieved accuracy comparable to ML with higher practicality. Excessive summer heat induces thermal expansion of railway rails, …

kr, jp (code pays fourni par la source)

Evaluating the Impact of Climate and Land-Use Change on Flood Susceptibility on a Global Scale

Fatemeh Rezaie, Saeid Janizadeh, Sayed Mohammadreza Bateni, Changhyun Jun et autres

us, ir, kr, Afrique du Sud, se, fr (code pays fourni par la source)