Landslide susceptibility modelling using different advanced decision trees methods

Optimized rule-based logistic model tree algorithm for mapping mangrove species using ALOS PALSAR imagery and GIS in the tropical region

(2018) Tien Dat Pham et al.   Environmental Earth Sciences

Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

(2018) Binh Thai Pham et al.   GEOMORPHOLOGY

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

Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran)

(2018) Sasan Vafaei et al.   Remote Sensing

A comparative study of sequential minimal optimization-based support vector machines, vote feature intervals, and logistic regression in landslide susceptibility assessment using GIS

(2017) Binh Thai Pham 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

GIS-based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naïve-Bayes tree, and alternating decision tree models

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

GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks

(2016) Dieu Tien Bui et al.   Environmental Earth Sciences

A novel ensemble classifier of rotation forest and Naïve Bayer for landslide susceptibility assessment at the Luc Yen district, Yen Bai Province (Viet Nam) using GIS

(2016) Binh Thai Pham et al.   Geomatics Natural Hazards & Risk

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

A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape

(2015) Kennedy Were et al.   ECOLOGICAL INDICATORS

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 random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia

(2015) Ahmed Mohamed Youssef et al.   Landslides

Shallow and Deep-Seated Landslide Differentiation Using Support Vector Machines: A Case Study of the Chuetsu Area, Japan

(2015) Jie Dou et al.   TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES

Land subsidence susceptibility mapping at Kinta Valley (Malaysia) using the evidential belief function model in GIS

(2014) Biswajeet Pradhan et al.   NATURAL HAZARDS

Estimating landslide susceptibility through a artificial neural network classifier

(2014) Paraskevas Tsangaratos et al.   NATURAL HAZARDS

Modeling and Testing Landslide Hazard Using Decision Tree

(2014) Mutasem Sh. Alkhasawneh et al.   Journal of Applied Mathematics

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

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

(2013) Taskin Kavzoglu et al.   Landslides

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

Predicting disease risks from highly imbalanced data using random forest

(2011) Mohammed Khalilia et al.   BMC Medical Informatics and Decision Making

New Combined S-transform and Logistic Model Tree Technique for Recognition and Classification of Power Quality Disturbances

(2011) Z. Moravej et al.   ELECTRIC POWER COMPONENTS AND SYSTEMS

Object-oriented mapping of landslides using Random Forests

(2011) André Stumpf et al.   REMOTE SENSING OF ENVIRONMENT

A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping

(2010) Mohammad H. Vahidnia et al.   COMPUTERS & GEOSCIENCES

Assessment of Landslide Susceptibility by Decision Trees in the Metropolitan Area of Istanbul, Turkey

(2010) H. A. Nefeslioglu et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine

(2009) Işık Yilmaz   Environmental Earth Sciences

Comparison of decision tree methods for finding active objects

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