GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method

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New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed (2019, background): “…(NBT) [5,52], radial basis function (RBF) [53], kernel logistic regression (KLR) [54,55], Bayes’ net (BN) [56], bivariate statistical index (SI) [57], stochastic gradient descent (SGD) [58], particle swarm optimization (PSO) [59], best-ﬁrst decision tree (BFDT) [60], random subspace-based…”
Evaluating the application of the statistical index method in flood susceptibility mapping and its comparison with frequency ratio and logistic regression methods (2018, background): “LR is one of the most popular MSA techniques for a variety of applications such as landslides (Chen et al. 2017), floods (Tehrany et al. 2017), land subsidence (Kim et al. 2006), earthquakes (Umar et al. 2014), mineral mapping (Xiong and Zuo 2018), and ground water mapping (Chen et al. 2018a).”
Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree (2019, background): “…et al. 2018), logistic regression (LR) (Colkesen et al. 2016; Aditian et al. 2018), multivariate adaptive regression spline (Zabihi et al. 2016; Chen et al. 2018d), weight of evidence (Tehrany et al. 2014; Guo et al. 2015), index of entropy (Tsangaratos et al. 2017; Chen et al. 2018c),…”