Can we detect trends in natural disaster management with artificial intelligence? A review of modeling practices
L Tan, J Guo, S Mohanarajah, K Zhou - Natural Hazards, 2021 - Springer
There has been an unsettling rise in the intensity and frequency of natural disasters due to
climate change and anthropogenic activities. Artificial intelligence (AI) models have shown …
climate change and anthropogenic activities. Artificial intelligence (AI) models have shown …
Comparison of a logistic regression and Naïve Bayes classifier in landslide susceptibility assessments: The influence of models complexity and training dataset size
The main objective of the present study was to compare the performance of a classifier that
implements the Logistic Regression and a classifier that employs a Naïve Bayes algorithm in …
implements the Logistic Regression and a classifier that employs a Naïve Bayes algorithm in …
Landslide susceptibility assessment in Lianhua County (China): a comparison between a random forest data mining technique and bivariate and multivariate …
Landslides are an important natural hazard that causes a great amount of damage around
the world every year, especially during the rainy season. The Lianhua area is located in the …
the world every year, especially during the rainy season. The Lianhua area is located in the …
Evaluation of prediction capability of the artificial neural networks for map** landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy)
Landslides are one of the most widespread natural hazards that cause damage to both
property and life every year, and therefore, the spatial distribution of the landslide …
property and life every year, and therefore, the spatial distribution of the landslide …
Risk assessment and its influencing factors analysis of geological hazards in typical mountain environment
J Lin, W Chen, X Qi, H Hou - Journal of cleaner production, 2021 - Elsevier
Fujian Province is a typical mountainous environment, where regional geological hazards
occur frequently, posing serious threats to the safety of local residents' lives and property …
occur frequently, posing serious threats to the safety of local residents' lives and property …
[HTML][HTML] Landslide susceptibility zonation using geospatial technique and analytical hierarchy process in Sikkim Himalaya
This study aims to delineate landslide susceptibility maps using an integrated approach of
remote sensing, geographical information system (GIS), and Analytical Hierarchy Process …
remote sensing, geographical information system (GIS), and Analytical Hierarchy Process …
Artificial neural network and sensitivity analysis in the landslide susceptibility map** of Idukki district, India
Idukki district faced adverse mishappenings during the 2018 Kerala landslides due to
incessant torrential rainfall. This study emphasizes develo** an efficient and accurate …
incessant torrential rainfall. This study emphasizes develo** an efficient and accurate …
GIS-based landslide spatial modeling in Ganzhou City, China
Landslide susceptibility map** is among the first works for disaster management and land
use planning activities in a mountain area like Ganzhou City. The aims of the current study …
use planning activities in a mountain area like Ganzhou City. The aims of the current study …
An objective absence data sampling method for landslide susceptibility map**
The accuracy and quality of the landslide susceptibility map depend on the available
landslide locations and the sampling strategy for absence data (non-landslide locations). In …
landslide locations and the sampling strategy for absence data (non-landslide locations). In …
Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models
C Polykretis, C Chalkias - Natural hazards, 2018 - Springer
The main purpose of this study is to compare the performance of two statistical analysis
models like weight of evidence and logistic regression (LR) with a soft computing model like …
models like weight of evidence and logistic regression (LR) with a soft computing model like …