Novel Credal Decision Tree-Based Ensemble Approaches for Predicting the Landslide Susceptibility

Assessing the Importance of Static and Dynamic Causative Factors on Erosion Potentiality Using SWAT, EBF with Uncertainty and Plausibility, Logistic Regression and Novel Ensemble Model in a Sub-tropical Environment

(2020) Rabin Chakrabortty et al.   Journal of the Indian Society of Remote Sensing

Landslide Susceptibility Evaluation and Management Using Different Machine Learning Methods in The Gallicash River Watershed, Iran

(2020) Alireza Arabameri et al.   Remote Sensing

Landslide Susceptibility Mapping: Machine and Ensemble Learning Based on Remote Sensing Big Data

(2020) Bahareh Kalantar et al.   Remote Sensing

Improvement of Credal Decision Trees Using Ensemble Frameworks for Groundwater Potential Modeling

(2020) Phong Tung Nguyen et al.   Sustainability

Evaluating the Performance of Individual and Novel Ensemble of Machine Learning and Statistical Models for Landslide Susceptibility Assessment at Rudraprayag District of Garhwal Himalaya

(2020) Sunil Saha et al.   Applied Sciences-Basel

GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran

(2020) Xinxiang Lei et al.   Remote Sensing

Comparison of Support Vector Machine, Bayesian Logistic Regression, and Alternating Decision Tree Algorithms for Shallow Landslide Susceptibility Mapping along a Mountainous Road in the West of Iran

(2020) Viet-Ha Nhu et al.   Applied Sciences-Basel

Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan

(2019) Jie Dou et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Novel Entropy and Rotation Forest-Based Credal Decision Tree Classifier for Landslide Susceptibility Modeling

(2019) Qingfeng He et al.   Entropy

Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility

(2019) Abolfazl Jaafari et al.   CATENA

Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm

(2019) Dieu Tien Bui et al.   Remote Sensing

Spatial prediction of landslide susceptibility in Taleghan basin, Iran

(2019) Maryam Mokhtari et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

Potential Landslide Vulnerability Zonation Using Integrated Analytic Hierarchy Process and GIS Technique of Upper Rangit Catchment Area, West Sikkim, India

(2019) Subodh Chandra Pal et al.   Journal of the Indian Society of Remote Sensing

Landslide Susceptibility Assessment by Novel Hybrid Machine Learning Algorithms

(2019) Pham et al.   Sustainability

Flood susceptibility mapping by ensemble evidential belief function and binomial logistic regression model on river basin of eastern India

(2019) Indrajit Chowdhuri et al.   ADVANCES IN SPACE RESEARCH

Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping

(2019) Yanli Wu et al.   CATENA

How accurate are the performances of gridded precipitation data products over Northeast China?

(2018) Muhammad Abrar Faiz et al.   ATMOSPHERIC RESEARCH

Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBFNetwork models for the Long County area (China)

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

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

Groundwater spring potential modelling: Comprising the capability and robustness of three different modeling approaches

(2018) Omid Rahmati et al.   JOURNAL OF HYDROLOGY

Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function-logistic regression algorithm

(2018) Alireza Arabameri et al.   LAND DEGRADATION & DEVELOPMENT

Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms

(2018) Dieu Tien Bui et al.   SENSORS

Application of Ensemble-Based Machine Learning Models to Landslide Susceptibility Mapping

(2018) Prima Kadavi et al.   Remote Sensing

Hybrid Integration Approach of Entropy with Logistic Regression and Support Vector Machine for Landslide Susceptibility Modeling

(2018) Tingyu Zhang et al.   Entropy

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

(2018) Binh Thai Pham et al.   CATENA

Applying different scenarios for landslide spatial modeling using computational intelligence methods

(2017) Alireza Arabameri et al.   Environmental Earth Sciences

A novel hybrid artificial intelligence approach for flood susceptibility assessment

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

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

(2017) Omid Rahmati et al.   GEOMORPHOLOGY

Improving transferability strategies for debris flow susceptibility assessment: Application to the Saponara and Itala catchments (Messina, Italy)

(2017) M. Cama et al.   GEOMORPHOLOGY

Landslide susceptibility mapping using random forest and boosted tree models in Pyeong-Chang, Korea

(2017) Jeong-Cheol Kim et al.   Geocarto International

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

Shallow Landslide Susceptibility Modeling Using the Data Mining Models Artificial Neural Network and Boosted Tree

(2017) Hyun-Joo Oh et al.   Applied Sciences-Basel

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

Random forests and evidential belief function-based landslide susceptibility assessment in Western Mazandaran Province, Iran

(2016) Hamid Reza Pourghasemi et al.   Environmental Earth Sciences

Water erosion susceptibility mapping by applying Stochastic Gradient Treeboost to the Imera Meridionale River Basin (Sicily, Italy)

(2016) Silvia Eleonora Angileri et al.   GEOMORPHOLOGY

Random forest in remote sensing: A review of applications and future directions

(2016) Mariana Belgiu et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Applying Information Theory and GIS-based quantitative methods to produce landslide susceptibility maps in Nancheng County, China

(2016) Paraskevas Tsangaratos et al.   Landslides

Application of frequency ratio, weights of evidence and evidential belief function models in landslide susceptibility mapping

(2016) Qingfeng Ding et al.   Geocarto International

Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study)

(2016) Rubini Mahalingam 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

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

Derivation of terrain covariates for digital soil mapping in Australia

(2015) John C. Gallant et al.   Soil Research

Spatial filtering to reduce sampling bias can improve the performance of ecological niche models

(2014) Robert A. Boria et al.   ECOLOGICAL MODELLING

A test of transferability for landslides susceptibility models under extreme climatic events: application to the Messina 2009 disaster

(2014) L. Lombardo et al.   NATURAL HAZARDS

Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale

(2014) Mustafa Neamah Jebur et al.   REMOTE SENSING OF ENVIRONMENT

Analysis and extension of decision trees based on imprecise probabilities: Application on noisy data

(2013) Carlos J. Mantas et al.   EXPERT SYSTEMS WITH APPLICATIONS

Gully erosion susceptibility assessment by means of GIS-based logistic regression: A case of Sicily (Italy)

(2013) Christian Conoscenti et al.   GEOMORPHOLOGY

An evaluation of SVM using polygon-based random sampling in landslide susceptibility mapping: The Candir catchment area (western Antalya, Turkey)

(2013) B. Taner San   International Journal of Applied Earth Observation and Geoinformation

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 mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran

(2012) Hamid Reza Pourghasemi et al.   CATENA

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

Integrating physical and empirical landslide susceptibility models using generalized additive models

(2011) Jason N. Goetz et al.   GEOMORPHOLOGY

Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)

(2011) Adnan Ozdemir   JOURNAL OF HYDROLOGY

Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

(2009) Tomáš Václavík et al.   ECOLOGICAL MODELLING

Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations, climates and methods of analysis on model sensitivity to crop parameters

(2009) Roberto Confalonieri et al.   ENVIRONMENTAL MODELLING & SOFTWARE

GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations

(2007) Ali Yalcin   CATENA

Three way k-fold cross-validation of resource selection functions

(2007) Trevor S. Wiens et al.   ECOLOGICAL MODELLING