[HTML][HTML] A review of ensemble learning algorithms used in remote sensing applications
Y Zhang, J Liu, W Shen - Applied Sciences, 2022 - mdpi.com
Machine learning algorithms are increasingly used in various remote sensing applications
due to their ability to identify nonlinear correlations. Ensemble algorithms have been …
due to their ability to identify nonlinear correlations. Ensemble algorithms have been …
[HTML][HTML] A review on interpretable and explainable artificial intelligence in hydroclimatic applications
This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable
Artificial Intelligence (XAI) models for data imputations and numerical or categorical …
Artificial Intelligence (XAI) models for data imputations and numerical or categorical …
A novel hybrid of meta-optimization approach for flash flood-susceptibility assessment in a monsoon-dominated watershed, Eastern India
The exponential growth in the number of flash flood events is a global threat, and detecting a
flood-prone area has also become a top priority. The flash flood-susceptibility mapping can …
flood-prone area has also become a top priority. The flash flood-susceptibility mapping can …
[HTML][HTML] Flooding and its relationship with land cover change, population growth, and road density
Bangladesh experiences frequent hydro-climatic disasters such as flooding. These disasters
are believed to be associated with land use changes and climate variability. However …
are believed to be associated with land use changes and climate variability. However …
[HTML][HTML] Flood susceptibility assessment using novel ensemble of hyperpipes and support vector regression algorithms
Recurrent floods are one of the major global threats among people, particularly in
developing countries like India, as this nation has a tropical monsoon type of climate …
developing countries like India, as this nation has a tropical monsoon type of climate …
[HTML][HTML] A hybrid of ensemble machine learning models with RFE and Boruta wrapper-based algorithms for flash flood susceptibility assessment
Flash floods are among the world most destructive natural disasters, and developing
optimum hybrid Machine Learning (ML) models for flash flood susceptibility (FFS) modeling …
optimum hybrid Machine Learning (ML) models for flash flood susceptibility (FFS) modeling …
Threats of climate change and land use patterns enhance the susceptibility of future floods in India
The main objective of this work is the future prediction of the floods in India due to climate
and land change. Human activity and related carbon emissions are the primary cause of …
and land change. Human activity and related carbon emissions are the primary cause of …
[HTML][HTML] Bim-based energy analysis and optimization using insight 360 (case study)
Building information modeling (BIM) is a modern data information platform and management
tool that promotes the development of green buildings. In Pakistan, the building sector …
tool that promotes the development of green buildings. In Pakistan, the building sector …
Multi-objective optimization of fly ash-slag based geopolymer considering strength, cost and CO2 emission: a new framework based on tree-based ensemble models …
Fly ash-slag based geopolymer has excellent mechanical performance with low carbon
footprints, which has emerged as a promising alternative to Portland cement. The …
footprints, which has emerged as a promising alternative to Portland cement. The …
Examining LightGBM and CatBoost models for wadi flash flood susceptibility prediction
This study presents two machine learning models, namely, the light gradient boosting
machine (LightGBM) and categorical boosting (CatBoost), for the first time for predicting …
machine (LightGBM) and categorical boosting (CatBoost), for the first time for predicting …