Predicting and analyzing flood susceptibility using boosting-based ensemble machine learning algorithms with SHapley Additive exPlanations
HE Aydin, MC Iban - Natural Hazards, 2023 - Springer
In recent years, the number of floods around the world has increased. As a result, Flood
Susceptibility Maps (FSMs) became vital for flood prevention, risk mitigation, and decision …
Susceptibility Maps (FSMs) became vital for flood prevention, risk mitigation, and decision …
Flood susceptibility mapping using hybrid models optimized with Artificial Bee Colony
K Plataridis, Z Mallios - Journal of Hydrology, 2023 - Elsevier
Floods are the most common type of natural hazard causing economic and human losses.
Mapping the susceptibility to flooding is essential for the effective management of flood risk …
Mapping the susceptibility to flooding is essential for the effective management of flood risk …
Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable development
Abstract Accurate prediction of Land Surface Temperature (LST) is critical for understanding
and mitigating the effects of climate change and land use dynamics. This study proposes a …
and mitigating the effects of climate change and land use dynamics. This study proposes a …
[HTML][HTML] Explainable artificial intelligence in disaster risk management: Achievements and prospective futures
Disasters can have devastating impacts on communities and economies, underscoring the
urgent need for effective strategic disaster risk management (DRM). Although Artificial …
urgent need for effective strategic disaster risk management (DRM). Although Artificial …
Role of national conditions in occupational fatal accidents in the construction industry using interpretable machine learning approach
K Koc - Journal of Management in Engineering, 2023 - ascelibrary.org
Current national occupational safety and health (OSH) initiatives follow reactive approaches,
ie, if it breaks, fix it. Existing accounts, however, failed to improve national OSH …
ie, if it breaks, fix it. Existing accounts, however, failed to improve national OSH …
Predicting cost impacts of nonconformances in construction projects using interpretable machine learning
Nonconformance (NCR) has long been a subject of research interest for its potential to
extrapolate information leading to a more productive environment in construction projects …
extrapolate information leading to a more productive environment in construction projects …
A new graph-based deep learning model to predict flooding with validation on a case study on the humber river
Floods are one of the most lethal natural disasters. It is crucial to forecast the timing and
evolution of these events and create an advanced warning system to allow for the proper …
evolution of these events and create an advanced warning system to allow for the proper …
Influencing factors and risk assessment of precipitation-induced flooding in Zhengzhou, China, based on random forest and XGBoost algorithms
X Liu, P Zhou, Y Lin, S Sun, H Zhang, W Xu… - International Journal of …, 2022 - mdpi.com
Due to extreme weather phenomena, precipitation-induced flooding has become a frequent,
widespread, and destructive natural disaster. Risk assessments of flooding have thus …
widespread, and destructive natural disaster. Risk assessments of flooding have thus …
Role of Shapley additive explanations and resampling algorithms for contract failure prediction of public–private partnership projects
K Koc - Journal of Management in Engineering, 2023 - ascelibrary.org
A public–private partnership (PPP) is a common procurement model implemented
worldwide as a catalyst for economic growth and improved public infrastructure. However …
worldwide as a catalyst for economic growth and improved public infrastructure. However …
Climate change induced disasters and highly vulnerable infrastructure in Uttarakhand, India: current status and way forward towards resilience and long-term …
The mountain state of Uttarakhand constitutes a part of the North-western Indian Himalayan
region and is inherently vulnerable to natural disasters. It is witnessing faster melting of …
region and is inherently vulnerable to natural disasters. It is witnessing faster melting of …