Related references
Note: Only part of the references are listed.Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan
Jie Dou et al.
LANDSLIDES (2020)
Landslide susceptibility assessment based on an incomplete landslide inventory in the Jilong Valley, Tibet, Chinese Himalayas
Juan Du et al.
ENGINEERING GEOLOGY (2020)
GIS-based ensemble soft computing models for landslide susceptibility mapping
Binh Thai Pham et al.
ADVANCES IN SPACE RESEARCH (2020)
Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
Abdelaziz Merghadi et al.
EARTH-SCIENCE REVIEWS (2020)
A comparison of statistical and machine learning methods for debris flow susceptibility mapping
Zhu Liang et al.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2020)
Classification and susceptibility assessment of debris flow based on a semi-quantitative method combination of the fuzzy C-means algorithm, factor analysis and efficacy coefficient
Zhu Liang et al.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2020)
Susceptibility assessment of landslides triggered by earthquakes in the Western Sichuan Plateau
Juan Cao et al.
CATENA (2019)
A novel hybrid model of Bagging-based Naive Bayes Trees for landslide susceptibility assessment
Binh Thai Pham et al.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2019)
Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)
Haoyuan Hong et al.
CATENA (2018)
Prediction of the landslide susceptibility: Which algorithm, which precision?
Hamid Reza Pourghasemi et al.
CATENA (2018)
A review of statistically-based landslide susceptibility models
Paola Reichenbach et al.
EARTH-SCIENCE REVIEWS (2018)
A comparison of statistical and deterministic methods for shallow landslide susceptibility zoning in clayey soils
Mariantonietta Ciurleo et al.
ENGINEERING GEOLOGY (2017)
Mapping landslide susceptibility using data-driven methods
J. L. Zezere et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2017)
Landslide susceptibility assessment using maximum entropy model with two different data sampling methods
Aiding Kornejady et al.
CATENA (2017)
A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility
Wei Chen et al.
CATENA (2017)
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
Ahmed Mohamed Youssef et al.
LANDSLIDES (2016)
Susceptibility zoning of shallow landslides in fine grained soils by statistical methods
Mariantonietta Ciurleo et al.
CATENA (2016)
Landslide distribution and size in response to Quaternary fault activity: the Peloritani Range, NE Sicily, Italy
Francesco Bucci et al.
EARTH SURFACE PROCESSES AND LANDFORMS (2016)
GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks
Dieu Tien Bui et al.
ENVIRONMENTAL EARTH SCIENCES (2016)
Landslides, threshold slopes, and the survival of relict terrain in the wake of the Mendocino Triple Junction
Georgina L. Bennett et al.
GEOLOGY (2016)
Different landslide sampling strategies in a grid-based bi-variate statistical susceptibility model
Haydar Y. Hussin et al.
GEOMORPHOLOGY (2016)
Susceptibility mapping of shallow landslides using kernel-based Gaussian process, support vector machines and logistic regression
Ismail Colkesen et al.
JOURNAL OF AFRICAN EARTH SCIENCES (2016)
Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines
Haoyuan Hong et al.
CATENA (2015)
Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling
J. N. Goetz et al.
COMPUTERS & GEOSCIENCES (2015)
Is the present the key to the future?
Stefano Furlani et al.
EARTH-SCIENCE REVIEWS (2015)
Landslide susceptibility mapping using ensemble bivariate and multivariate statistical models in Fayfa area, Saudi Arabia
Ahmed M. Youssef et al.
ENVIRONMENTAL EARTH SCIENCES (2015)
Debris-flow susceptibility assessment at regional scale: Validation on an alpine environment
Francesco Bregoli et al.
LANDSLIDES (2015)
Landslide susceptibility assessment using object mapping units, decision tree, and support vector machine models in the Three Gorges of China
Xueling Wu et al.
ENVIRONMENTAL EARTH SCIENCES (2014)
GIS-based ordered weighted averaging and Dempster-Shafer methods for landslide susceptibility mapping in the Urmia Lake Basin, Iran
Bakhtiar Feizizadeh et al.
INTERNATIONAL JOURNAL OF DIGITAL EARTH (2014)
Assessment of M5′ model tree and classification and regression trees for prediction of scour depth below free overfall spillways
Mehrshad Samadi et al.
NEURAL COMPUTING & APPLICATIONS (2014)
Extreme learning machine for the displacement prediction of landslide under rainfall and reservoir level
Cheng Lian et al.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2014)
Sample size matters: investigating the effect of sample size on a logistic regression susceptibility model for debris flows
T. Heckmann et al.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2014)
Landslide susceptibility assessment in the Hoa Binh province of Vietnam: A comparison of the Levenberg-Marquardt and Bayesian regularized neural networks
Dieu Tien Bui et al.
GEOMORPHOLOGY (2012)
Letter to the Editor: Stability of Random Forest importance measures
M. L. Calle et al.
BRIEFINGS IN BIOINFORMATICS (2010)
Landslide Susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches
B. Pradhan
JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING (2010)
Data clustering: 50 years beyond K-means
Anil K. Jain
PATTERN RECOGNITION LETTERS (2010)
An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps
H. A. Nefeslioglu et al.
ENGINEERING GEOLOGY (2008)
Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview
Cees J. van Westen et al.
ENGINEERING GEOLOGY (2008)
Geomorphology and landslide susceptibility assessment using GIS and bivariate statistics: a case study in southern Italy
Paolo Magliulo et al.
NATURAL HAZARDS (2008)
Comparing SOM neural network with Fuzzy c-means, K-means and traditional hierarchical clustering algorithms
Sueli A. Mingoti et al.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2006)
Landslide hazard assessment in the Collazzone area, Umbria, Central Italy
F Guzzetti et al.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2006)
The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan
L Ayalew et al.
GEOMORPHOLOGY (2005)
Validation of spatial prediction models for landslide hazard mapping
CJF Chung et al.
NATURAL HAZARDS (2003)
Greedy function approximation: A gradient boosting machine
JH Friedman
ANNALS OF STATISTICS (2001)
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
TG Dietterich
MACHINE LEARNING (2000)