Application of hybrid machine learning-based ensemble techniques for rainfall-runoff modeling
G Gelete - Earth Science Informatics, 2023 - Springer
The main aim of this study was to develop hybrid machine learning (ML)-based ensemble
modeling of the rainfall-runoff process in the Katar catchment, Ethiopia. This study used four …
modeling of the rainfall-runoff process in the Katar catchment, Ethiopia. This study used four …
An intelligent soft computing technique for prediction of vehicular traffic noise
A reliable vehicular traffic noise model is essential for both monitoring and management of
environmental noise pollution. In this study, Gaussian process regression (GPR), feed …
environmental noise pollution. In this study, Gaussian process regression (GPR), feed …
Hybrid extreme gradient boosting and nonlinear ensemble models for suspended sediment load prediction in an agricultural catchment
G Gelete - Water Resources Management, 2023 - Springer
In this study, four individual models namely Hammerstein-Weiner (HW), Extreme Learning
Machine (ELM), Long Short-Term Memory (LSTM) and Least Square Support Vector …
Machine (ELM), Long Short-Term Memory (LSTM) and Least Square Support Vector …
Determining susceptible body parts of construction workers due to occupational injuries using inclusive modelling
Despite significant progress has been made in safety management practices, construction
industry still accounts for a substantial number of occupational accidents leading to injuries …
industry still accounts for a substantial number of occupational accidents leading to injuries …
[HTML][HTML] Prediction of chloride diffusion coefficient in concrete modified with supplementary cementitious materials using machine learning algorithms
AF Al Fuhaid, H Alanazi - Materials, 2023 - mdpi.com
The chloride diffusion coefficient (Dcl) is one of the most important characteristics of concrete
durability. This study aimed to develop a prediction model for the Dcl of concrete …
durability. This study aimed to develop a prediction model for the Dcl of concrete …
[HTML][HTML] Tiered prediction models for port vessel emissions inventories
Albeit its importance, a large number of port authorities do not provide continuous or publicly
available air emissions inventories (EIs) and thereby obscure the emissions contribution of …
available air emissions inventories (EIs) and thereby obscure the emissions contribution of …
[HTML][HTML] Drought Forecasting Using Integrated Variational Mode Decomposition and Extreme Gradient Boosting
Ö Ekmekcioğlu - Water, 2023 - mdpi.com
The current study seeks to conduct time series forecasting of droughts by means of the state-
of-the-art XGBoost algorithm. To explore the drought variability in one of the semi-arid …
of-the-art XGBoost algorithm. To explore the drought variability in one of the semi-arid …
Physical and artificial intelligence-based hybrid models for rainfall–runoff–sediment process modelling
This study evaluates the performance of the Hydrologic Engineering Center-Hydrologic
Modelling System (HEC-HMS), Hydrologiska Byråns Vattenbalansavdelning (HBV), Soil and …
Modelling System (HEC-HMS), Hydrologiska Byråns Vattenbalansavdelning (HBV), Soil and …
[HTML][HTML] Comparison and integration of physical and interpretable AI-driven models for rainfall-runoff simulation
S Asadi, P Jimeno-Sáez, A López-Ballesteros… - Results in …, 2024 - Elsevier
Precise streamflow forecasting in river systems is crucial for water resources management
and flood risk assessment. The Tagus Headwaters River Basin (THRB) in Spain is a key …
and flood risk assessment. The Tagus Headwaters River Basin (THRB) in Spain is a key …
[HTML][HTML] Development of Artificial Intelligence Based Safety Performance Measures for Urban Roundabouts
A reliable model for predicting crash frequency at roundabouts is an essential tool for
evaluating the safety measures of a roundabout. This study developed a hybrid PSO-ANN …
evaluating the safety measures of a roundabout. This study developed a hybrid PSO-ANN …