Artificial neural networks applied to landslide susceptibility: The effect of sampling areas on model capacity for generalization and extrapolation

A hybrid model considering spatial heterogeneity for landslide susceptibility mapping in Zhejiang Province, China

(2020) Yumiao Wang et al.   CATENA

Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping

(2020) Zhice Fang et al.   COMPUTERS & GEOSCIENCES

Exploring the effects of the design and quantity of absence data on the performance of random forest-based landslide susceptibility mapping

(2019) Haoyuan Hong et al.   CATENA

Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms

(2019) Qingfeng He et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China

(2019) Yi Wang et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction

(2019) Nguyen et al.   Applied Sciences-Basel

Random forest and artificial neural networks in landslide susceptibility modeling: a case study of the Fão River Basin, Southern Brazil

(2019) Guilherme Garcia de Oliveira et al.   NATURAL HAZARDS

Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment

(2019) Maher Ibrahim Sameen et al.   CATENA

Review on landslide susceptibility mapping using support vector machines

(2018) Yu Huang et al.   CATENA

Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China

(2018) Wei Chen et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Application and comparison of logistic regression model and neural network model in earthquake-induced landslides susceptibility mapping at mountainous region, China

(2018) Peng Xie et al.   Geomatics Natural Hazards & Risk

Comparison of the presence-only method and presence-absence method in landslide susceptibility mapping

(2018) A-Xing Zhu et al.   CATENA

The artificial neural network for the rockfall susceptibility assessment. A case study in Basilicata (Southern Italy)

(2018) Lucia Losasso et al.   Geomatics Natural Hazards & Risk

A ROC analysis-based classification method for landslide susceptibility maps

(2018) Isidro Cantarino et al.   Landslides

A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)

(2017) Haoyuan Hong et al.   Environmental Earth Sciences

Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques

(2017) Wei Chen et al.   GEODERMA

Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion

(2017) Omid Rahmati et al.   GEOMORPHOLOGY

Landslide susceptibility mapping & prediction using Support Vector Machine for Mandakini River Basin, Garhwal Himalaya, India

(2017) Deepak Kumar et al.   GEOMORPHOLOGY

Characterization and quantification of path dependency in landslide susceptibility

(2017) Jalal Samia et al.   GEOMORPHOLOGY

Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)

(2017) Bahareh Kalantar et al.   Geomatics Natural Hazards & Risk

GIS-based landslide spatial modeling in Ganzhou City, China

(2016) Haoyuan Hong et al.   Arabian Journal of Geosciences

Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling

(2015) J.N. Goetz et al.   COMPUTERS & GEOSCIENCES

Simplifying artificial neural network models of river basin behaviour by an automated procedure for input variable selection

(2015) Guilherme G. Oliveira et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Development of hybrid wavelet packet-statistical models (WP-SM) for landslide susceptibility mapping

(2015) Vahid Moosavi et al.   Landslides

Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree

(2015) Dieu Tien Bui et al.   Landslides

Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

(2015) Himan Shahabi et al.   Scientific Reports

Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression

(2013) Taskin Kavzoglu et al.   Landslides

Landslide susceptibility mapping at Zonouz Plain, Iran using genetic programming and comparison with frequency ratio, logistic regression, and artificial neural network models

(2013) Vahid Nourani et al.   NATURAL HAZARDS

GIS-based landslide susceptibility mapping using analytic hierarchy process and artificial neural network in Jeju (Korea)

(2012) He-Chun Quan et al.   KSCE Journal of Civil Engineering

Plausibility test of conceptual soil maps using relief parameters

(2011) Markus Möller et al.   CATENA

A new method of pseudo absence data generation in landslide susceptibility mapping with a case study of Shenzhen

(2011) ChenChao Xiao et al.   Science China-Technological Sciences

Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia

(2009) Biswajeet Pradhan et al.   Landslides

Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China

(2008) X. Yao et al.   GEOMORPHOLOGY

Placing soil-genesis and transport processes into a landscape context: A multiscale terrain-analysis approach

(2008) Markus Möller et al.   JOURNAL OF PLANT NUTRITION AND SOIL SCIENCE

Comparing landslide inventory maps

(2007) Mirco Galli et al.   GEOMORPHOLOGY