Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam
Authors
Keywords
-
Journal
Geocarto International
Volume -, Issue -, Pages 1-24
Publisher
Informa UK Limited
Online
2019-09-18
DOI
10.1080/10106049.2019.1665715
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Landslide susceptibility modelling using different advanced decision trees methods
- (2019) Binh Thai Pham et al. CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS
- Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM
- (2019) Jie Dou et al. Remote Sensing
- Wildfire Probability Mapping: Bivariate vs. Multivariate Statistics
- (2019) Abolfazl Jaafari et al. Remote Sensing
- 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
- Exploring the effects of the design and quantity of absence data on the performance of random forest-based landslide susceptibility mapping
- (2019) Haoyuan Hong et al. CATENA
- Predicting spatial patterns of wildfire susceptibility in the Huichang County, China: An integrated model to analysis of landscape indicators
- (2019) Haoyuan Hong et al. ECOLOGICAL INDICATORS
- Torrential rainfall-triggered shallow landslide characteristics and susceptibility assessment using ensemble data-driven models in the Dongjiang Reservoir Watershed, China
- (2019) Jie Dou et al. NATURAL HAZARDS
- Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models
- (2019) Nohani et al. Water
- Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis
- (2019) Binh Thai Pham et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Hybrid computational intelligence models for groundwater potential mapping
- (2019) Binh Thai Pham et al. CATENA
- A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling
- (2018) Binh Thai Pham et al. Bulletin of Engineering Geology and the Environment
- Wildfire spatial pattern analysis in the Zagros Mountains, Iran: A comparative study of decision tree based classifiers
- (2018) Abolfazl Jaafari et al. Ecological Informatics
- Developing robust arsenic awareness prediction models using machine learning algorithms
- (2018) Sushant K. Singh et al. JOURNAL OF ENVIRONMENTAL MANAGEMENT
- A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran
- (2018) Khabat Khosravi et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Landslide susceptibility assessment in the Anfu County, China: comparing different statistical and probabilistic models considering the new topo-hydrological factor (HAND)
- (2018) Haoyuan Hong et al. Earth Science Informatics
- A novel method for landslide displacement prediction by integrating advanced computational intelligence algorithms
- (2018) Chao Zhou et al. Scientific Reports
- A Comparison of Support Vector Machines and Bayesian Algorithms for Landslide Susceptibility Modeling
- (2018) Binh Thai Pham et al. Geocarto International
- Improving Landslide Detection from Airborne Laser Scanning Data Using Optimized Dempster–Shafer
- (2018) Mustafa Mezaal et al. Remote Sensing
- Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach
- (2018) Shaghayegh Miraki et al. WATER RESOURCES MANAGEMENT
- Landslide Detection and Susceptibility Mapping by AIRSAR Data Using Support Vector Machine and Index of Entropy Models in Cameron Highlands, Malaysia
- (2018) Dieu Tien Bui et al. Remote Sensing
- Landslide susceptibility assessment at the Wuning area, China: a comparison between multi-criteria decision making, bivariate statistical and machine learning methods
- (2018) Haoyuan Hong et al. NATURAL HAZARDS
- Mapping earthquake-triggered landslide susceptibility by use of artificial neural network (ANN) models: an example of the 2013 Minxian (China) Mw 5.9 event
- (2018) Yingying Tian et al. Geomatics Natural Hazards & Risk
- Landslide Susceptibility Modeling Based on GIS and Novel Bagging-Based Kernel Logistic Regression
- (2018) Wei Chen et al. Applied Sciences-Basel
- Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches
- (2018) Binh Thai Pham et al. CATENA
- Rock fall susceptibility assessment along a mountainous road: an evaluation of bivariate statistic, analytical hierarchy process and frequency ratio
- (2017) Ataollah Shirzadi et al. Environmental Earth Sciences
- Shallow landslide susceptibility assessment using a novel hybrid intelligence approach
- (2017) Ataollah Shirzadi et al. Environmental Earth Sciences
- Evaluation and comparison of LogitBoost Ensemble, Fisher’s Linear Discriminant Analysis, logistic regression and support vector machines methods for landslide susceptibility mapping
- (2017) Binh Thai Pham 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
- Application of BP Neural Network Algorithm in Traditional Hydrological Model for Flood Forecasting
- (2017) Jianjin Wang et al. Water
- Application of time series analysis and PSO–SVM model in predicting the Bazimen landslide in the Three Gorges Reservoir, China
- (2016) Chao Zhou et al. ENGINEERING GEOLOGY
- A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India)
- (2016) Binh Thai Pham et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization: a case study in Central Vietnam
- (2016) Dieu Tien Bui et al. International Journal of Digital Earth
- A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping
- (2016) Wei Chen et al. Geocarto International
- 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
- A new hybrid model using step-wise weight assessment ratio analysis (SWARA) technique and adaptive neuro-fuzzy inference system (ANFIS) for regional landslide hazard assessment in Iran
- (2015) Alireza Dehnavi et al. CATENA
- Spatial prediction of landslide hazard at the Luxi area (China) using support vector machines
- (2015) Haoyuan Hong et al. Environmental Earth Sciences
- 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 multi-criteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh
- (2014) Bayes Ahmed Landslides
- Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms
- (2013) Mohammad Zare et al. Arabian Journal of Geosciences
- Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models
- (2013) Himan Shahabi et al. CATENA
- Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression
- (2013) Taskin Kavzoglu et al. Landslides
- Machine Learning Feature Selection Methods for Landslide Susceptibility Mapping
- (2013) Natan Micheletti et al. Mathematical Geosciences
- 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
- Global patterns of loss of life from landslides
- (2012) David Petley GEOLOGY
- Pliocene-to-present morphotectonics of the Dien Bien Phu fault in northwest Vietnam
- (2012) Kuang-Yin Lai et al. GEOMORPHOLOGY
- 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
- Landslide susceptibility assessment using SVM machine learning algorithm
- (2011) Miloš Marjanović et al. ENGINEERING GEOLOGY
- An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia
- (2011) Masoud Bakhtyari Kia et al. Environmental Earth Sciences
- GIS-based spatial prediction of landslide susceptibility using logistic regression model
- (2011) Seyedeh Zohreh Mousavi et al. Geomatics Natural Hazards & Risk
- Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system
- (2010) Hyun-Joo Oh et al. Environmental Earth Sciences
- 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
- Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India)
- (2009) Iswar Das et al. GEOMORPHOLOGY
- Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China
- (2008) X. Yao et al. GEOMORPHOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started