GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam
出版年份 2019 全文链接
标题
GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam
作者
关键词
-
出版物
Sustainability
Volume 11, Issue 24, Pages 7118
出版商
MDPI AG
发表日期
2019-12-13
DOI
10.3390/su11247118
参考文献
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 bee colony-based neural network for the prediction of the fundamental period of infilled frame structures
- (2019) Panagiotis G. Asteris et al. NEURAL COMPUTING & APPLICATIONS
- 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
- An Ensemble Model for Landslide Susceptibility Mapping in a Forested Area
- (2019) Alireza Arabameri et al. Geocarto International
- GIS and AHP Techniques Based Delineation of Groundwater Potential Zones: a case study from Southern Western Ghats, India
- (2019) P. Arulbalaji et al. Scientific Reports
- A New Approach Using AHP to Generate Landslide Susceptibility Maps in the Chen-Yu-Lan Watershed, Taiwan
- (2019) Thi Nguyen et al. SENSORS
- Novel Entropy and Rotation Forest-Based Credal Decision Tree Classifier for Landslide Susceptibility Modeling
- (2019) Qingfeng He et al. Entropy
- Spatial pattern analysis and prediction of forest fire using new machine learning approach of Multivariate Adaptive Regression Splines and Differential Flower Pollination optimization: A case study at Lao Cai province (Viet Nam)
- (2019) Dieu Tien Bui et al. JOURNAL OF ENVIRONMENTAL MANAGEMENT
- Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms
- (2019) Qingfeng He et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Hybrid Artificial Intelligence Approaches for Predicting Buckling Damage of Steel Columns Under Axial Compression
- (2019) Lu Minh Le et al. Materials
- Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees
- (2019) Ly et al. Materials
- Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models
- (2019) Hui Chen et al. Applied Sciences-Basel
- Landslide Susceptibility Mapping Based on Random Forest and Boosted Regression Tree Models, and a Comparison of Their Performance
- (2019) Soyoung Park et al. Applied Sciences-Basel
- Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns
- (2019) Payam Sarir et al. ENGINEERING WITH COMPUTERS
- Performance Analysis of Advanced Decision Tree-Based Ensemble Learning Algorithms for Landslide Susceptibility Mapping
- (2019) Emrehan Kutlug Sahin et al. Geocarto International
- Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models
- (2019) Nohani et al. Water
- Prediction of Surface Treatment Effects on the Tribological Performance of Tool Steels Using Artificial Neural Networks
- (2019) Liborio Cavaleri et al. Applied Sciences-Basel
- Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam
- (2019) Tran Van Phong et al. Geocarto International
- Landslide Susceptibility Assessment by Novel Hybrid Machine Learning Algorithms
- (2019) Pham et al. Sustainability
- Prediction Success of Machine Learning Methods for Flash Flood Susceptibility Mapping in the Tafresh Watershed, Iran
- (2019) Saeid Janizadeh et al. Sustainability
- Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete
- (2019) Ly et al. Applied Sciences-Basel
- Spatial prediction of shallow landslide using Bat algorithm optimized machine learning approach: A case study in Lang Son Province, Vietnam
- (2019) Dieu Tien Bui et al. ADVANCED ENGINEERING INFORMATICS
- Hybrid computational intelligence models for groundwater potential mapping
- (2019) Binh Thai Pham et al. CATENA
- Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques
- (2019) Kuan-Tsung Chang et al. Scientific Reports
- Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach
- (2019) Chongchong Qi et al. CHEMOSPHERE
- Wildfire spatial pattern analysis in the Zagros Mountains, Iran: A comparative study of decision tree based classifiers
- (2018) Abolfazl Jaafari et al. Ecological Informatics
- Bagging based Support Vector Machines for spatial prediction of landslides
- (2018) Binh Thai Pham et al. Environmental Earth Sciences
- Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia
- (2018) Aril Aditian et al. GEOMORPHOLOGY
- Spatial Prediction of Rainfall-Induced Landslides Using Aggregating One-Dependence Estimators Classifier
- (2018) Binh Thai Pham et al. Journal of the Indian Society of Remote Sensing
- Krill herd algorithm-based neural network in structural seismic reliability evaluation
- (2018) Panagiotis G. Asteris et al. MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
- 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
- A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment
- (2018) Khabat Khosravi et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping
- (2018) Ataollah Shirzadi et al. SENSORS
- Landslide Susceptibility Modeling Based on GIS and Novel Bagging-Based Kernel Logistic Regression
- (2018) Wei Chen et al. Applied Sciences-Basel
- A novel artificial intelligence approach based on Multi-layer Perceptron Neural Network and Biogeography-based Optimization for predicting coefficient of consolidation of soil
- (2018) Binh Thai Pham et al. CATENA
- Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches
- (2018) Binh Thai Pham et al. CATENA
- A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)
- (2017) Haoyuan Hong et al. Environmental Earth Sciences
- Shallow landslide susceptibility assessment using a novel hybrid intelligence approach
- (2017) Ataollah Shirzadi et al. Environmental Earth Sciences
- A novel hybrid artificial intelligence approach for flood susceptibility assessment
- (2017) Kamran Chapi et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Self-compacting concrete strength prediction using surrogate models
- (2017) Panagiotis G. Asteris et al. NEURAL COMPUTING & APPLICATIONS
- Application of Support Vector Machine, Random Forest, and Genetic Algorithm Optimized Random Forest Models in Groundwater Potential Mapping
- (2017) Seyed Amir Naghibi et al. WATER RESOURCES MANAGEMENT
- GIS-based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naïve-Bayes tree, and alternating decision tree models
- (2017) Wei Chen et al. Geomatics Natural Hazards & Risk
- 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
- Spatial data analysis and application of evidential belief functions to shallow landslide susceptibility mapping at Mt. Umyeon, Seoul, Korea
- (2016) Ananta Man Singh Pradhan et al. Bulletin of Engineering Geology and the Environment
- Comparison of a logistic regression and Naïve Bayes classifier in landslide susceptibility assessments: The influence of models complexity and training dataset size
- (2016) Paraskevas Tsangaratos et al. CATENA
- 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
- Landslide Hazard Assessment Using Random SubSpace Fuzzy Rules Based Classifier Ensemble and Probability Analysis of Rainfall Data: A Case Study at Mu Cang Chai District, Yen Bai Province (Viet Nam)
- (2016) Binh Thai Pham et al. Journal of the Indian Society of Remote Sensing
- Spatial prediction of rainfall-induced landslides for the Lao Cai area (Vietnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization
- (2016) Dieu Tien Bui et al. Landslides
- Rotation forest fuzzy rule-based classifier ensemble for spatial prediction of landslides using GIS
- (2016) Binh Thai Pham et al. NATURAL HAZARDS
- 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
- 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 assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural networks, and functional trees methods
- (2015) Binh Thai Pham et al. THEORETICAL AND APPLIED CLIMATOLOGY
- Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression
- (2013) Taskin Kavzoglu et al. Landslides
- Comparison of different models for susceptibility mapping of earthquake triggered landslides related with the 2008 Wenchuan earthquake in China
- (2012) Chong Xu et al. COMPUTERS & GEOSCIENCES
- Application of an evidential belief function model in landslide susceptibility mapping
- (2012) Omar F. Althuwaynee et al. COMPUTERS & GEOSCIENCES
- Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal
- (2012) P. Kayastha et al. COMPUTERS & GEOSCIENCES
- Characterising performance of environmental models
- (2012) Neil D. Bennett et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Support Vector Machines for Landslide Susceptibility Mapping: The Staffora River Basin Case Study, Italy
- (2012) Cristiano Ballabio et al. Mathematical Geosciences
- Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran
- (2012) Hamid Reza Pourghasemi et al. NATURAL HAZARDS
- Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area
- (2011) Hyun-Joo Oh et al. COMPUTERS & GEOSCIENCES
- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
- (2011) M. Galar et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE
- Landslide susceptibility mapping in Injae, Korea, using a decision tree
- (2010) Young-Kwang Yeon et al. ENGINEERING GEOLOGY
- Landslide Susceptibility Mapping by Neuro-Fuzzy Approach in a Landslide-Prone Area (Cameron Highlands, Malaysia)
- (2010) Biswajeet Pradhan et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling
- (2009) Biswajeet Pradhan et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China
- (2008) X. Yao et al. GEOMORPHOLOGY
- Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey)
- (2007) Hakan A. Nefeslioglu et al. GEOMORPHOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now