[HTML][HTML] Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer
As threats of landslide hazards have become gradually more severe in recent decades,
studies on landslide prevention and mitigation have attracted widespread attention in …
studies on landslide prevention and mitigation have attracted widespread attention in …
GIS-based flood hazard mapping using relative frequency ratio method: A case study of Panjkora River Basin, eastern Hindu Kush, Pakistan
K Ullah, J Zhang - Plos one, 2020 - journals.plos.org
Flood is the most devastating and prevalent disaster among all-natural disasters. Every year,
flood claims hundreds of human lives and causes damage to the worldwide economy and …
flood claims hundreds of human lives and causes damage to the worldwide economy and …
[HTML][HTML] Landslide susceptibility mapping with deep learning algorithms
Among natural hazards, landslides are devastating in China. However, little is known
regarding potential landslide-prone areas in Maoxian County. The goal of this study was to …
regarding potential landslide-prone areas in Maoxian County. The goal of this study was to …
Comparisons of convolutional neural network and other machine learning methods in landslide susceptibility assessment: a case study in Pingwu
Z Jiang, M Wang, K Liu - Remote Sensing, 2023 - mdpi.com
Landslide is a natural disaster that seriously affects human life and social development. In
this study, the characteristics and effectiveness of convolutional neural network (CNN) and …
this study, the characteristics and effectiveness of convolutional neural network (CNN) and …
Spatial prediction of landslides using hybrid integration of artificial intelligence algorithms with frequency ratio and index of entropy in nanzheng county, china
W Chen, L Fan, C Li, BT Pham - Applied Sciences, 2019 - mdpi.com
The main object of this study is to introduce hybrid integration approaches that consist of
state-of-the-art artificial intelligence algorithms (SysFor) and two bivariate models, namely …
state-of-the-art artificial intelligence algorithms (SysFor) and two bivariate models, namely …
Multi-temporal land cover change mapping using google earth engine and ensemble learning methods
The study deals with the application of Google Earth Engine (GEE), Landsat data and
ensemble-learning methods (ELMs) to map land cover (LC) change over a decade in the …
ensemble-learning methods (ELMs) to map land cover (LC) change over a decade in the …
Landslide development within 3 years after the 2015 Mw 7.8 Gorkha earthquake, Nepal
Abstract The Araniko and Pasang Lhamu highways are two critical trading routes connecting
Nepal and China that are experiencing and are threatened by landsliding. The April 25 M w …
Nepal and China that are experiencing and are threatened by landsliding. The April 25 M w …
Mapping groundwater potential zones using relative frequency ratio, analytic hierarchy process and their hybrid models: case of Nzhelele-Makhado area in South …
N Muavhi, KH Thamaga, MI Mutoti - Geocarto International, 2022 - Taylor & Francis
Identification of groundwater potential zones (GWPZ) is as equally important as determining
the most effective groundwater mapping models for efficient production of reliable GWPZ …
the most effective groundwater mapping models for efficient production of reliable GWPZ …
Landslide susceptibility mapping using deep learning models in Ardabil province, Iran
Landslides are one of the most destructive natural phenomena in the world, which occur
mostly in mountainous areas and cause damage to the economic sectors, agricultural lands …
mostly in mountainous areas and cause damage to the economic sectors, agricultural lands …
[HTML][HTML] Assessment of landslide susceptibility along the araniko highway in poiqu/bhote koshi/sun koshi watershed, Nepal himalaya
Landslide susceptibility assessment along the Araniko highway was done using the
relationship between the landslide causative factor and presence/absence of landslide …
relationship between the landslide causative factor and presence/absence of landslide …