GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and …
Flood is a devastating natural hazard that may cause damage to the environment
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …
A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area
This research proposes and evaluates a new approach for flash flood susceptibility mapping
based on Deep Learning Neural Network (DLNN)) algorithm, with a case study at a high …
based on Deep Learning Neural Network (DLNN)) algorithm, with a case study at a high …
Flash-flood susceptibility assessment using multi-criteria decision making and machine learning supported by remote sensing and GIS techniques
Concerning the significant increase in the negative effects of flash-floods worldwide, the
main goal of this research is to evaluate the power of the Analytical Hierarchy Process …
main goal of this research is to evaluate the power of the Analytical Hierarchy Process …
Multi-criteria decision based geospatial mapping of flood susceptibility and temporal hydro-geomorphic changes in the Subarnarekha basin, India
Abstract The Subarnarekha River in east India experiences frequent high magnitude
flooding in monsoon season. In this study, we present an in-depth analysis of flood …
flooding in monsoon season. In this study, we present an in-depth analysis of flood …
[HTML][HTML] Flash flood susceptibility modelling using soft computing-based approaches: from bibliometric to meta-data analysis and future research directions
In recent years, there has been a growing interest in flood susceptibility modeling. In this
study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the …
study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the …
Geographic information system and AHP-based flood hazard zonation of Vaitarna basin, Maharashtra, India
S Das - Arabian Journal of Geosciences, 2018 - Springer
Flood is one of the most common natural hazard that take place almost everywhere around
the world except the polar regions. Flood damage can be reduced through implementing …
the world except the polar regions. Flood damage can be reduced through implementing …
Identification of areas prone to flash-flood phenomena using multiple-criteria decision-making, bivariate statistics, machine learning and their ensembles
R Costache, DT Bui - Science of the Total Environment, 2020 - Elsevier
Taking into account the exponential growth of the number of flash-floods events worldwide,
the detection of areas prone to these natural hazards is one of the main activities taken in …
the detection of areas prone to these natural hazards is one of the main activities taken in …
Comparative assessment of the flash-flood potential within small mountain catchments using bivariate statistics and their novel hybrid integration with machine …
R Costache, H Hong, QB Pham - Science of the Total Environment, 2020 - Elsevier
The present study is carried out in the context of the continuous increase, worldwide, of the
number of flash-floods phenomena. Also, there is an evident increase of the size of the …
number of flash-floods phenomena. Also, there is an evident increase of the size of the …
Spatial prediction of flood potential using new ensembles of bivariate statistics and artificial intelligence: A case study at the Putna river catchment of Romania
R Costache, DT Bui - Science of The Total Environment, 2019 - Elsevier
Flash-flood is considered to be one of the most destructive natural hazards in the world,
which is difficult to accurately model and predict. The objective of the present research is to …
which is difficult to accurately model and predict. The objective of the present research is to …
Spatial predicting of flood potential areas using novel hybridizations of fuzzy decision-making, bivariate statistics, and machine learning
The global warming and climate changes determined a considerable increase in the
frequency of floods and their related damages. Therefore, the high accuracy prediction of …
frequency of floods and their related damages. Therefore, the high accuracy prediction of …