A comparative study of support vector machine and logistic model tree classifiers for shallow landslide susceptibility modeling

Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree

(2019) Wei Chen et al.   Geocarto International

Hybrid Machine Learning Approaches for Landslide Susceptibility Modeling

(2019) Vu Nguyen et al.   Forests

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

Uncertainties of prediction accuracy in shallow landslide modeling: Sample size and raster resolution

(2019) Ataollah Shirzadi et al.   CATENA

Review on landslide susceptibility mapping using support vector machines

(2018) Yu Huang et al.   CATENA

Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)

(2018) Haoyuan Hong et al.   CATENA

A hybrid machine learning ensemble approach based on a Radial Basis Function neural network and Rotation Forest for landslide susceptibility modeling: A case study in the Himalayan area, India

(2018) Binh Thai Pham et al.   International Journal of Sediment Research

Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping

(2018) Hossein Shafizadeh-Moghadam et al.   JOURNAL OF ENVIRONMENTAL MANAGEMENT

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran

(2018) Khabat Khosravi et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution

(2018) Haoyuan Hong et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Flood susceptibility assessment using integration of adaptive network-based fuzzy inference system (ANFIS) and biogeography-based optimization (BBO) and BAT algorithms (BA)

(2018) M. Ahmadlou et al.   Geocarto International

A novel ensemble approach of bivariate statistical-based logistic model tree classifier for landslide susceptibility assessment

(2018) Wei Chen et al.   Geocarto International

A Novel Hybrid Approach of Bayesian Logistic Regression and Its Ensembles for Landslide Susceptibility Assessment

(2018) Mousa Abedini et al.   Geocarto International

Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms

(2018) Dieu Tien Bui et al.   SENSORS

Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach

(2018) Shaghayegh Miraki et al.   WATER RESOURCES MANAGEMENT

Novel Hybrid Evolutionary Algorithms for Spatial Prediction of Floods

(2018) Dieu Tien Bui et al.   Scientific Reports

Landslide Detection and Susceptibility Mapping by AIRSAR Data Using Support Vector Machine and Index of Entropy Models in Cameron Highlands, Malaysia

(2018) Dieu Tien Bui et al.   Remote Sensing

A Novel Integrated Approach of Relevance Vector Machine Optimized by Imperialist Competitive Algorithm for Spatial Modeling of Shallow Landslides

(2018) Dieu Tien Bui et al.   Remote Sensing

New Hybrids of ANFIS with Several Optimization Algorithms for Flood Susceptibility Modeling

(2018) Dieu Tien Bui et al.   Water

Novel hybrid artificial intelligence approach of bivariate statistical-methods-based kernel logistic regression classifier for landslide susceptibility modeling

(2018) Wei Chen et al.   Bulletin of Engineering Geology and the Environment

Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping

(2018) Ataollah Shirzadi et al.   SENSORS

A Novel Hybrid Approach of Landslide Susceptibility Modeling Using Rotation Forest Ensemble and Different Base Classifiers

(2018) Binh Thai Pham et al.   Geocarto International

Landslide Susceptibility Modeling Based on GIS and Novel Bagging-Based Kernel Logistic Regression

(2018) Wei Chen et al.   Applied Sciences-Basel

Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches

(2018) Binh Thai Pham et al.   CATENA

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

Rock fall susceptibility assessment along a mountainous road: an evaluation of bivariate statistic, analytical hierarchy process and frequency ratio

(2017) Ataollah Shirzadi et al.   Environmental Earth Sciences

Landslide susceptibility mapping in Bijar city, Kurdistan Province, Iran: a comparative study by logistic regression and AHP models

(2017) M. Abedini et al.   Environmental Earth Sciences

Shallow landslide susceptibility assessment using a novel hybrid intelligence approach

(2017) Ataollah Shirzadi et al.   Environmental Earth Sciences

A novel hybrid artificial intelligence approach for flood susceptibility assessment

(2017) Kamran Chapi et al.   ENVIRONMENTAL MODELLING & SOFTWARE

A hybrid fuzzy weight of evidence method in landslide susceptibility analysis on the Wuyuan area, China

(2017) Haoyuan Hong et al.   GEOMORPHOLOGY

A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China

(2017) Wei Chen et al.   Geomatics Natural Hazards & Risk

Integration of the Statistical Index Method and the Analytic Hierarchy Process technique for the assessment of landslide susceptibility in Huizhou, China

(2016) Guifang Zhang et al.   CATENA

A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India)

(2016) Binh Thai Pham et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models

(2016) Haoyuan Hong et al.   GEOMORPHOLOGY

Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines

(2015) Haoyuan Hong et al.   CATENA

Landslide susceptibility mapping using a modified decision tree classifier in the Xanthi Perfection, Greece

(2015) Paraskevas Tsangaratos 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 assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural networks, and functional trees methods

(2015) Binh Thai Pham et al.   THEORETICAL AND APPLIED CLIMATOLOGY

An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district

(2014) Taskin Kavzoglu et al.   NATURAL HAZARDS

Gain ratio based fuzzy weighted association rule mining classifier for medical diagnostic interface

(2014) N S NITHYA et al.   SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES

Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya

(2013) Amar Deep Regmi et al.   Arabian Journal of Geosciences

Landslide susceptibility mapping based on rough set theory and support vector machines: A case of the Three Gorges area, China

(2013) Ling Peng et al.   GEOMORPHOLOGY

Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran

(2013) HAMID REZA POURGHASEMI et al.   Journal of Earth System Science

A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

(2012) Biswajeet Pradhan   COMPUTERS & GEOSCIENCES

The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling

(2012) Chong Xu et al.   Environmental Earth Sciences

Characterising performance of environmental models

(2012) Neil D. Bennett et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Landslide susceptibility mapping along road corridors in the Indian Himalayas using Bayesian logistic regression models

(2012) Iswar Das et al.   GEOMORPHOLOGY

Support Vector Machines for Landslide Susceptibility Mapping: The Staffora River Basin Case Study, Italy

(2012) Cristiano Ballabio et al.   Mathematical Geosciences

Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naïve Bayes Models

(2012) Dieu Tien Bui et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

A GIS-based logistic regression model in rock-fall susceptibility mapping along a mountainous road: Salavat Abad case study, Kurdistan, Iran

(2012) Ataollah Shirzadi et al.   NATURAL HAZARDS

Decision tree approach for classification and dimensionality reduction of electronic nose data

(2011) Jung Hwan Cho et al.   SENSORS AND ACTUATORS B-CHEMICAL

GIS-based spatial prediction of landslide susceptibility using logistic regression model

(2011) Seyedeh Zohreh Mousavi et al.   Geomatics Natural Hazards & Risk

Landslide-susceptibility mapping in a semi-arid mountain environment: an example from the southern slopes of Sierra Nevada (Granada, Spain)

(2010) J. D. Jiménez-Perálvarez et al.   Bulletin of Engineering Geology and the Environment

Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia

(2010) Biswajeet Pradhan   Environmental Earth Sciences

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

(2008) X. Yao et al.   GEOMORPHOLOGY

Comparison of decision tree methods for finding active objects

(2007) Yongheng Zhao et al.   ADVANCES IN SPACE RESEARCH