相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Artificial neural network ensembles applied to the mapping of landslide susceptibility
L. Bragagnolo et al.
CATENA (2020)
Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment
Maher Ibrahim Sameen et al.
CATENA (2020)
Evaluation of the extreme rainfall predictions and their impact on landslide susceptibility in a sub-catchment scale
Keh-Jian Shou et al.
ENGINEERING GEOLOGY (2020)
Machine learning and fractal theory models for landslide susceptibility mapping: Case study from the Jinsha River Basin
Qiao Hu et al.
GEOMORPHOLOGY (2020)
Optimizing the frequency ratio method for landslide susceptibility assessment: A case study of the Caiyuan Basin in the southeast mountainous area of China
Yi-xing Zhang et al.
JOURNAL OF MOUNTAIN SCIENCE (2020)
Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning
Jie Dou et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2020)
Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment
Dieu Tien Bui et al.
CATENA (2020)
Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping
Yanli Wu et al.
CATENA (2020)
Landslide Susceptibility Evaluation and Management Using Different Machine Learning Methods in The Gallicash River Watershed, Iran
Alireza Arabameri et al.
REMOTE SENSING (2020)
Comparative study of landslide susceptibility mapping with different recurrent neural networks
Yi Wang et al.
COMPUTERS & GEOSCIENCES (2020)
Spatial Prediction of Landslide Susceptibility Based on GIS and Discriminant Functions
Guirong Wang et al.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2020)
Mapping landslide susceptibility at the Three Gorges Reservoir, China, using gradient boosting decision tree, random forest and information value models
Chen Tao et al.
JOURNAL OF MOUNTAIN SCIENCE (2020)
Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping
Zhice Fang et al.
COMPUTERS & GEOSCIENCES (2020)
Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
Abdelaziz Merghadi et al.
EARTH-SCIENCE REVIEWS (2020)
Landslide susceptibility mapping using multiscale sampling strategy and convolutional neural network: A case study in Jiuzhaigou region
Yaning Yi et al.
CATENA (2020)
A comparison of Support Vector Machines and Bayesian algorithms for landslide susceptibility modelling
Binh T. Pham et al.
GEOCARTO INTERNATIONAL (2019)
Optimization of causative factors using logistic regression and artificial neural network models for landslide susceptibility assessment in Ujung Loe Watershed, South Sulawesi Indonesia
Andang Suryana Soma et al.
JOURNAL OF MOUNTAIN SCIENCE (2019)
Parameter investigation of support vector machine classifier with kernel functions
Alaa Tharwat
KNOWLEDGE AND INFORMATION SYSTEMS (2019)
Predictive modeling of landslide hazards in Wen County, northwestern China based on information value, weights-of-evidence, and certainty factor
Qiqing Wang et al.
GEOMATICS NATURAL HAZARDS & RISK (2019)
Exploring the effects of the design and quantity of absence data on the performance of random forest-based landslide susceptibility mapping
Haoyuan Hong et al.
CATENA (2019)
GIS-based logistic regression for rainfall-induced landslide susceptibility mapping under different grid sizes in Yueqing, Southeastern China
Yu Zhao et al.
ENGINEERING GEOLOGY (2019)
Comparing probabilistic and statistical methods in landslide susceptibility modeling in Rwanda/Centre-Eastern Africa
Jean Baptiste Nsengiyumva et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2019)
Landslide spatial modelling using novel bivariate statistical based Naive Bayes, RBF Classifier, and RBF Network machine learning algorithms
Qingfeng He et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2019)
Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China
Yi Wang et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2019)
Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm
Dieu Tien Bui et al.
REMOTE SENSING (2019)
Landslide Susceptibility Mapping Based on Random Forest and Boosted Regression Tree Models, and a Comparison of Their Performance
Soyoung Park et al.
APPLIED SCIENCES-BASEL (2019)
Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models
Ebrahim Nohani et al.
WATER (2019)
A Novel Performance Assessment Approach Using Photogrammetric Techniques for Landslide Susceptibility Mapping with Logistic Regression, ANN and Random Forest
Eray Sevgen et al.
SENSORS (2019)
Spatial Prediction of Landslide Susceptibility Using GIS-Based Data Mining Techniques of ANFIS with Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO)
Wei Chen et al.
APPLIED SCIENCES-BASEL (2019)
Landslide Susceptibility Mapping Using GIS-Based Data Mining Algorithms
Vali Vakhshoori et al.
WATER (2019)
Performance evaluation for four GIS-based models purposed to predict and map landslide susceptibility: A case study at a World Heritage site in Southwest China
Yuanmei Jiao et al.
CATENA (2019)
Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan
Jie Dou et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2019)
Innovative landslide susceptibility mapping supported by geomorphon and geographical detector methods
Wei Luo et al.
LANDSLIDES (2018)
Comparison of machine-learning techniques for landslide susceptibility mapping using two-level random sampling (2LRS) in Alakir catchment area, Antalya, Turkey
Metehan Ada et al.
NATURAL HAZARDS (2018)
Review on landslide susceptibility mapping using support vector machines
Yu Huang et al.
CATENA (2018)
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)
Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China
Chao Zhou et al.
COMPUTERS & GEOSCIENCES (2018)
A review of statistically-based landslide susceptibility models
Paola Reichenbach et al.
EARTH-SCIENCE REVIEWS (2018)
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
Binh Thai Pham et al.
INTERNATIONAL JOURNAL OF SEDIMENT RESEARCH (2018)
Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms
Dieu Tien Bui et al.
SENSORS (2018)
Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping
Ataollah Shirzadi et al.
SENSORS (2018)
Assessment of Landslide-Prone Areas and Their Zonation Using Logistic Regression, LogitBoost, and NaiveBayes Machine-Learning Algorithms
Hamid Reza Pourghasemi et al.
SUSTAINABILITY (2018)
Landslide Susceptibility Modeling Based on GIS and Novel Bagging-Based Kernel Logistic Regression
Wei Chen et al.
APPLIED SCIENCES-BASEL (2018)
Mapping landslide susceptibility and types using Random Forest
Khaled Taalab et al.
BIG EARTH DATA (2018)
Landslide susceptibility mapping & prediction using Support Vector Machine for Mandakini River Basin, Garhwal Himalaya, India
Deepak Kumar et al.
GEOMORPHOLOGY (2017)
Evaluating effectiveness of frequency ratio, fuzzy logic and logistic regression models in assessing landslide susceptibility: a case from Rudraprayag district, India
Mehebub Sahana et al.
JOURNAL OF MOUNTAIN SCIENCE (2017)
Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed, Gansu Province, China
Du Guo-liang et al.
JOURNAL OF MOUNTAIN SCIENCE (2017)
A GIS-based comparative evaluation of analytical hierarchy process and frequency ratio models for landslide susceptibility mapping
Qiqing Wang et al.
PHYSICAL GEOGRAPHY (2017)
GIS-based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naive-Bayes tree, and alternating decision tree models
Wei Chen et al.
GEOMATICS NATURAL HAZARDS & RISK (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)
Spatial prediction of landslide hazard at the Luxi area (China) using support vector machines
Haoyuan Hong et al.
ENVIRONMENTAL EARTH SCIENCES (2016)
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)
A comparative study for landslide susceptibility mapping using GIS-based multi-criteria decision analysis (MCDA), logistic regression (LR) and association rule mining (ARM)
Arzu Erener et al.
ENGINEERING GEOLOGY (2016)
Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models
Haoyuan Hong 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)
Landslide susceptibility mapping by comparing weight of evidence, fuzzy logic, and frequency ratio methods
V. Vakhshoori et al.
GEOMATICS NATURAL HAZARDS & RISK (2016)
Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling
J. N. Goetz et al.
COMPUTERS & GEOSCIENCES (2015)
Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)
Alessandro Trigila et al.
GEOMORPHOLOGY (2015)
Landslide susceptibility assessment of the Youfang catchment using logistic regression
Bai Shi-biao et al.
JOURNAL OF MOUNTAIN SCIENCE (2015)
Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment
Qianqian Wang et al.
SUSTAINABILITY (2015)
Landslide susceptibility mapping based on GIS and information value model for the Chencang District of Baoji, China
Wei Chen et al.
ARABIAN JOURNAL OF GEOSCIENCES (2014)
Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models
Himan Shahabi et al.
CATENA (2014)
Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression
Taskin Kavzoglu et al.
LANDSLIDES (2014)
A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS
Biswajeet Pradhan
COMPUTERS & GEOSCIENCES (2013)
A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey
Adnan Ozdemir et al.
JOURNAL OF ASIAN EARTH SCIENCES (2013)
Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues
F. Catani et al.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2013)
Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran
Hamid Reza Pourghasemi et al.
CATENA (2012)
Application of an evidential belief function model in landslide susceptibility mapping
Omar F. Althuwaynee et al.
COMPUTERS & GEOSCIENCES (2012)
Landslide susceptibility mapping along road corridors in the Indian Himalayas using Bayesian logistic regression models
Iswar Das et al.
GEOMORPHOLOGY (2012)
A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at Izmir, Turkey
Aykut Akgun
LANDSLIDES (2012)
Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naive Bayes Models
Dieu Tien Bui et al.
MATHEMATICAL PROBLEMS IN ENGINEERING (2012)
Landslide susceptibility assessment using SVM machine learning algorithm
Milos Marjanovic et al.
ENGINEERING GEOLOGY (2011)
Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression
Dieu Tien Bui et al.
NATURAL HAZARDS (2011)
A kernel functions analysis for support vector machines for land cover classification
T. Kavzoglu et al.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2009)
Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China
X. Yao et al.
GEOMORPHOLOGY (2008)
Building Predictive Models in R Using the caret Package
Max Kuhn
JOURNAL OF STATISTICAL SOFTWARE (2008)
Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models
Saro Lee et al.
LANDSLIDES (2007)
Spatial prediction models for landslide hazards: review, comparison and evaluation
A Brenning
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2005)
Landslide susceptibility mapping using GIS and the weight-of-evidence model
S Lee et al.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (2004)
Validation of spatial prediction models for landslide hazard mapping
CJF Chung et al.
NATURAL HAZARDS (2003)