A deep learning approach using graph convolutional networks for slope deformation prediction based on time-series displacement data

Suitability of data preprocessing methods for landslide displacement forecasting

(2020) Zongxing Zou et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

A Deep Learning approach for Path Prediction in a Location-based IoT system

(2020) Francesco Piccialli et al.   Pervasive and Mobile Computing

Machine learning for landslides prevention: a survey

(2020) Zhengjing Ma et al.   NEURAL COMPUTING & APPLICATIONS

A survey on deep learning in medicine: Why, how and when?

(2020) Francesco Piccialli et al.   Information Fusion

Time series analysis and long short-term memory neural network to predict landslide displacement

(2019) Beibei Yang et al.   Landslides

A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction

(2019) Faming Huang et al.   Landslides

Times-series data augmentation and deep learning for construction equipment activity recognition

(2019) Khandakar M. Rashid et al.   ADVANCED ENGINEERING INFORMATICS

Modeling and predicting reservoir landslide displacement with deep belief network and EWMA control charts: a case study in Three Gorges Reservoir

(2019) Huajin Li et al.   Landslides

A Survey of Internet of Things (IoT) for Geohazard Prevention: Applications, Technologies, and Challenges

(2019) Gang Mei et al.   IEEE Internet of Things Journal

T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction

(2019) Ling Zhao et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Displacement prediction of Baijiabao landslide based on empirical mode decomposition and long short-term memory neural network in Three Gorges area, China

(2018) Shiluo Xu et al.   COMPUTERS & GEOSCIENCES

A physical model predicting instability of rock slopes with locked segments along a potential slip surface

(2018) Hongran Chen et al.   ENGINEERING GEOLOGY

Displacement prediction of step-like landslide by applying a novel kernel extreme learning machine method

(2018) Chao Zhou et al.   Landslides

Landslide time-of-failure forecast and alert threshold assessment: A generalized criterion

(2018) A. Segalini et al.   ENGINEERING GEOLOGY

Early warning system using tilt sensors in Chibo, Kalimpong, Darjeeling Himalayas, India

(2018) Abhirup Dikshit et al.   NATURAL HAZARDS

Detection of American Football Head Impacts Using Biomechanical Features and Support Vector Machine Classification

(2018) Lyndia C. Wu et al.   Scientific Reports

An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction

(2018) Zaher Mundher Yaseen et al.   JOURNAL OF HYDROLOGY

Landslide displacement prediction based on multivariate chaotic model and extreme learning machine

(2017) Faming Huang et al.   ENGINEERING GEOLOGY

Comparison of two optimized machine learning models for predicting displacement of rainfall-induced landslide: A case study in Sichuan Province, China

(2017) Xing Zhu et al.   ENGINEERING GEOLOGY

Prediction of shallow landslide by surficial stability analysis considering rainfall infiltration

(2017) Sung Eun Cho   ENGINEERING GEOLOGY

Stability of intact slopes with tensile strength cut-off

(2017) R. L. Michalowski   GEOTECHNIQUE

Establishment of a deformation forecasting model for a step-like landslide based on decision tree C5.0 and two-step cluster algorithms: a case study in the Three Gorges Reservoir area, China

(2017) Junwei Ma et al.   Landslides

Prediction of landslide displacement with step-like behavior based on multialgorithm optimization and a support vector regression model

(2017) Fasheng Miao et al.   Landslides

Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction

(2016) Haitham Abdulmohsin Afan et al.   JOURNAL OF HYDROLOGY

Displacement prediction of landslide based on generalized regression neural networks with K -fold cross-validation

(2016) Ping Jiang et al.   NEUROCOMPUTING

Influencing factor analysis and displacement prediction in reservoir landslides − a case study of Three Gorges Reservoir (China)

(2016)   Tehnicki Vjesnik-Technical Gazette

Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

(2016) Farzad Fahimi et al.   THEORETICAL AND APPLIED CLIMATOLOGY

Analysis and prediction of aperiodic hydrodynamic oscillatory time series by feed-forward neural networks, fuzzy logic, and a local nonlinear predictor

(2015) Pier Luigi Gentili et al.   CHAOS

Multiple neural networks switched prediction for landslide displacement

(2015) Cheng Lian et al.   ENGINEERING GEOLOGY

Monitoring landslide displacements with the Geocube wireless network of low-cost GPS

(2015) L. Benoit et al.   ENGINEERING GEOLOGY

Artificial intelligence based models for stream-flow forecasting: 2000–2015

(2015) Zaher Mundher Yaseen et al.   JOURNAL OF HYDROLOGY

Quantification of model uncertainty in debris flow vulnerability assessment

(2014) U.M.K. Eidsvig et al.   ENGINEERING GEOLOGY

Early Warning Monitoring of Natural and Engineered Slopes with Ground-Based Synthetic-Aperture Radar

(2014) C. Atzeni et al.   ROCK MECHANICS AND ROCK ENGINEERING

Comparison on landslide nonlinear displacement analysis and prediction with computational intelligence approaches

(2013) Zaobao Liu et al.   Landslides

Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression

(2013) Taskin Kavzoglu et al.   Landslides

Early warning systems for natural hazards and risks

(2013) Thomas Glade et al.   NATURAL HAZARDS

Prediction of time to slope failure: a general framework

(2011) A. Federico et al.   Environmental Earth Sciences

A novel distributed optic fiber transduser for landslides monitoring

(2011) Zheng-Wei Zhu et al.   OPTICS AND LASERS IN ENGINEERING

Wavelets on graphs via spectral graph theory

(2010) David K. Hammond et al.   APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS