Rainfall induced landslide studies in Indian Himalayan region: a critical review
Landslides are one of the most devastating and recurring natural disasters and have
affected several mountainous regions across the globe. The Indian Himalayan region is no …
affected several mountainous regions across the globe. The Indian Himalayan region is no …
Coupling RBF neural network with ensemble learning techniques for landslide susceptibility map**
Using multiple ensemble learning techniques for improving the predictive accuracy of
landslide models is an active research area. In this study, we combined a radial basis …
landslide models is an active research area. In this study, we combined a radial basis …
Exploring effectiveness of frequency ratio and support vector machine models in storm surge flood susceptibility assessment: A study of Sundarban Biosphere …
Abstract The Sundarban Biosphere Reserve (SBR), which is one of the important coastal
regions of India, is vulnerable to storm surge hazards. It experiences storm surge flood of …
regions of India, is vulnerable to storm surge hazards. It experiences storm surge flood of …
Comparing classical statistic and machine learning models in landslide susceptibility map** in Ardanuc (Artvin), Turkey
Landslide susceptibility maps provide crucial information that helps local authorities, public
institutions, and land-use planners make the correct decisions when they are managing …
institutions, and land-use planners make the correct decisions when they are managing …
A comparison of frequency ratio and fuzzy logic models for flood susceptibility assessment of the lower Kosi River Basin in India
The Kosi megafan region of eastern Bihar, India, comprising of eight districts, is regularly
afflicted by large floods that cause extensive damage. Map** the possible inundation …
afflicted by large floods that cause extensive damage. Map** the possible inundation …
Ensemble modeling of landslide susceptibility using random subspace learner and different decision tree classifiers
In this study, we have developed five spatially explicit ensemble predictive machine learning
models for the landslide susceptibility map** of the Van Chan district of the Yen Bai …
models for the landslide susceptibility map** of the Van Chan district of the Yen Bai …
GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India
Predicting landslides is becoming a crucial global challenge for sustainable development in
mountainous areas. This research compares the landslide susceptibility maps (LSMs) …
mountainous areas. This research compares the landslide susceptibility maps (LSMs) …
Landslide susceptibility evaluation using hybrid integration of evidential belief function and machine learning techniques
Y Li, W Chen - Water, 2019 - mdpi.com
In this study, Random SubSpace-based classification and regression tree (RSCART) was
introduced for landslide susceptibility modeling, and CART model and logistic regression …
introduced for landslide susceptibility modeling, and CART model and logistic regression …
Ensemble machine learning models based on Reduced Error Pruning Tree for prediction of rainfall-induced landslides
In this paper, we developed highly accurate ensemble machine learning models integrating
Reduced Error Pruning Tree (REPT) as a base classifier with the Bagging (B), Decorate (D) …
Reduced Error Pruning Tree (REPT) as a base classifier with the Bagging (B), Decorate (D) …
Map** the susceptibility to landslides based on the deep belief network: a case study in Sichuan Province, China
A dataset of landslides from Sichuan Province in China, containing 1551 historical individual
landslides, is a result of two teams' effort in the past few years to map the susceptibility to …
landslides, is a result of two teams' effort in the past few years to map the susceptibility to …