Susceptibility Mapping on Urban Landslides Using Deep Learning Approaches in Mt. Umyeon

Optimizing the frequency ratio method for landslide susceptibility assessment: A case study of the Caiyuan Basin in the southeast mountainous area of China

(2020) Yi-xing Zhang et al.   Journal of Mountain Science

Optimizing an Adaptive Neuro-Fuzzy Inference System for Spatial Prediction of Landslide Susceptibility Using Four State-of-the-art Metaheuristic Techniques

(2020) Mohammad Mehrabi et al.   SENSORS

Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms

(2020) Viet-Ha Nhu et al.   International Journal of Environmental Research and Public Health

Modeling the effect of sediment concentration on the flow-like behavior of natural debris flow

(2020) Leonardo Schippa   International Journal of Sediment Research

Landslide Susceptibility Mapping Using the Slope Unit for Southeastern Helong City, Jilin Province, China: A Comparison of ANN and SVM

(2020) Chenglong Yu et al.   Symmetry-Basel

Review on remote sensing methods for landslide detection using machine and deep learning

(2020) Amrita Mohan et al.   Transactions on Emerging Telecommunications Technologies

Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection

(2019) Omid Ghorbanzadeh et al.   Remote Sensing

A State-of-the-Art Survey on Deep Learning Theory and Architectures

(2019) Md Zahangir Alom et al.   Electronics

An Ensemble Model for Landslide Susceptibility Mapping in a Forested Area

(2019) Alireza Arabameri et al.   Geocarto International

Hybrid Machine Learning Approaches for Landslide Susceptibility Modeling

(2019) Vu Nguyen et al.   Forests

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

(2019) Alireza Arabameri et al.   Journal of Mountain Science

Optimization of causative factors using logistic regression and artificial neural network models for landslide susceptibility assessment in Ujung Loe Watershed, South Sulawesi Indonesia

(2019) Andang Suryana Soma et al.   Journal of Mountain Science

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

Deep learning and its application in geochemical mapping

(2019) Renguang Zuo et al.   EARTH-SCIENCE REVIEWS

Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China

(2019) Yi Wang et al.   SCIENCE OF THE TOTAL ENVIRONMENT

GIS-based landslide susceptibility mapping using hybrid integration approaches of fractal dimension with index of entropy and support vector machine

(2019) Ting-yu Zhang et al.   Journal of Mountain Science

Deep Learning for Classification of Hyperspectral Data: A Comparative Review

(2019) Nicolas Audebert et al.   IEEE Geoscience and Remote Sensing Magazine

A comparative study of support vector machine and logistic model tree classifiers for shallow landslide susceptibility modeling

(2019) Mousa Abedini et al.   Environmental Earth Sciences

A novel voting ensemble model for spatial prediction of landslides using GIS

(2019) Shruti Sachdeva et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Reliability-based design for debris flow barriers

(2019) Federico Vagnon et al.   Landslides

Design of active debris flow mitigation measures: a comprehensive analysis of existing impact models

(2019) Federico Vagnon   Landslides

A Novel Performance Assessment Approach using Photogrammetric Techniques for Landslide Susceptibility Mapping with Logistic Regression, ANN and Random Forest

(2019) Sevgen et al.   SENSORS

UAV-Based Slope Failure Detection Using Deep-Learning Convolutional Neural Networks

(2019) Omid Ghorbanzadeh et al.   Remote Sensing

Landslide Susceptibility Assessment by Novel Hybrid Machine Learning Algorithms

(2019) Pham et al.   Sustainability

Landslide Susceptibility Evaluation Using Hybrid Integration of Evidential Belief Function and Machine Learning Techniques

(2019) Yang Li et al.   Water

A hybrid method for improved stability prediction in construction projects: A case study of stope hangingwall stability

(2018) Chongchong Qi et al.   APPLIED SOFT COMPUTING

Analysis and evaluation of landslide susceptibility: a review on articles published during 2005–2016 (periods of 2005–2012 and 2013–2016)

(2018) Hamid Reza Pourghasemi et al.   Arabian Journal of Geosciences

Modification of landslide susceptibility mapping using optimized PSO-ANN technique

(2018) Hossein Moayedi et al.   ENGINEERING WITH COMPUTERS

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 Mapping and Comparison Using Decision Tree Models: A Case Study of Jumunjin Area, Korea

(2018) Sung-Jae Park et al.   Remote Sensing

A laboratory experience on the effect of grains concentration and coarse sediment on the rheology of natural debris-flows

(2018) Anna Maria Pellegrino et al.   Environmental Earth Sciences

GIS-based fully automatic landslide susceptibility analysis by weight-of-evidence and frequency ratio methods

(2018) Derya Dilara Kose et al.   PHYSICAL GEOGRAPHY

A novel hybrid approach for landslide susceptibility mapping integrating analytical hierarchy process and normalized frequency ratio methods with the cloud model

(2018) Fei Yan et al.   GEOMORPHOLOGY

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

(2018) Binh Thai Pham et al.   CATENA

A survey of deep neural network architectures and their applications

(2017) Weibo Liu et al.   NEUROCOMPUTING

Data Mining Approaches for Landslide Susceptibility Mapping in Umyeonsan, Seoul, South Korea

(2017) Sunmin Lee et al.   Applied Sciences-Basel

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

Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran)

(2016) Iman Nasiri Aghdam et al.   Environmental Earth Sciences

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

Forecasting and validation of landslide susceptibility using an integration of frequency ratio and neuro-fuzzy models: a case study of Seorak mountain area in Korea

(2015) Moung-Jin Lee et al.   Environmental Earth Sciences

Deep learning

(2015) Yann LeCun et al.   NATURE

The slope aspect: A predisposing factor for landsliding?

(2014) Marco Capitani et al.   COMPTES RENDUS GEOSCIENCE

Modeling of groundwater recharge using a multiple linear regression (MLR) recharge model developed from geophysical parameters: a case of groundwater resources management

(2014) Kehinde Anthony Mogaji et al.   Environmental Earth Sciences

Debris flow in metropolitan area — 2011 Seoul debris flow

(2013) Chan-Young Yune et al.   Journal of Mountain Science

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

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

An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps

(2008) H.A. Nefeslioglu et al.   ENGINEERING GEOLOGY

GIS analysis to assess landslide susceptibility in a fluvial basin of NW Sicily (Italy)

(2007) Christian Conoscenti et al.   GEOMORPHOLOGY