[HTML][HTML] Unraveling the interactions between flooding dynamics and agricultural productivity in a changing climate
T Rupngam, AJ Messiga - Sustainability, 2024 - mdpi.com
Extreme precipitation and flooding frequency associated with global climate change are
expected to increase worldwide, with major consequences in floodplains and areas …
expected to increase worldwide, with major consequences in floodplains and areas …
Advanced hyperparameter optimization for improved spatial prediction of shallow landslides using extreme gradient boosting (XGBoost)
T Kavzoglu, A Teke - Bulletin of Engineering Geology and the Environment, 2022 - Springer
Abstract Machine learning algorithms have progressively become a part of landslide
susceptibility map** practices owing to their robustness in dealing with complicated and …
susceptibility map** practices owing to their robustness in dealing with complicated and …
Explainable step-wise binary classification for the susceptibility assessment of geo-hydrological hazards
Ö Ekmekcioğlu, K Koc - Catena, 2022 - Elsevier
This research proposes a novel step-wise binary prediction framework for the susceptibility
assessment of geo-hydrological hazards specific to floods and landslides. The framework of …
assessment of geo-hydrological hazards specific to floods and landslides. The framework of …
A novel flood risk management approach based on future climate and land use change scenarios
Climate change and increasing urbanization are two primary factors responsible for the
increased risk of serious flooding around the world. The prediction and monitoring of the …
increased risk of serious flooding around the world. The prediction and monitoring of the …
Multi‐hazard assessment using machine learning and remote sensing in the North Central region of Vietnam
Natural hazards constitute a diverse category and are unevenly distributed in time and
space. This hinders predictive efforts, leading to significant impacts on human life and …
space. This hinders predictive efforts, leading to significant impacts on human life and …
A step toward considering the return period in flood spatial modeling
In recent years, there has been an increasing interest in spatial modeling, and flood hazard
prediction is a major area of interest within the field of hydrology. It is necessary to consider …
prediction is a major area of interest within the field of hydrology. It is necessary to consider …
Artificial intelligence algorithms in flood prediction: a general overview
M Pandey - Geo-information for Disaster Monitoring and …, 2024 - Springer
This paper presents a comprehensive general overview of the extensive literature available
in the field of application of artificial intelligence (AI) in flood prediction. The initial approach …
in the field of application of artificial intelligence (AI) in flood prediction. The initial approach …
Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region, Türkiye
The impact of climate change has led to significant changes in hydroclimatic patterns and
continuous stress on water resources through frequent wet and dry spells. Hence …
continuous stress on water resources through frequent wet and dry spells. Hence …
Improving the prediction of wildfire susceptibility on Hawaiʻi Island, Hawaiʻi, using explainable hybrid machine learning models
This study presents a comparative analysis of four Machine Learning (ML) models used to
map wildfire susceptibility on Hawaiʻi Island, Hawaiʻi. Extreme Gradient Boosting …
map wildfire susceptibility on Hawaiʻi Island, Hawaiʻi. Extreme Gradient Boosting …
Travel time prediction and explanation with spatio-temporal features: A comparative study
Travel time information is used as input or auxiliary data for tasks such as dynamic
navigation, infrastructure planning, congestion control, and accident detection. Various data …
navigation, infrastructure planning, congestion control, and accident detection. Various data …