A5038013289- earthquake and tectonic studies
- Geological and Geochemical Analysis
- Geological and Geophysical Studies
- Flood Risk Assessment and Management
- Landslides and related hazards
- Fire effects on ecosystems
- Tree Root and Stability Studies
- Radioactive contamination and transfer
- High-pressure geophysics and materials
- Geochemistry and Geologic Mapping
- Hydrology and Watershed Management Studies
- Radioactivity and Radon Measurements
- Geological formations and processes
- Hydrological Forecasting Using AI
- Groundwater and Watershed Analysis
- Research studies in Vietnam
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Geophysics and Gravity Measurements
- Dam Engineering and Safety
- Cryospheric studies and observations
- Geological Modeling and Analysis
- Mineralogy and Gemology Studies
- Remote Sensing and Land Use
- Environmental Changes in China
- Seismic Imaging and Inversion Techniques
Vietnam Academy of Science and Technology
2016-2025
Hanoi University of Science and Technology
2021-2024
Institute of Geological Sciences
2022-2024
Institute of Geology of Ore Deposits Petrography Mineralogy and Geochemistry
2015
Instytut Nauk Geologicznych
2015
University of California, Los Angeles
2001
Science and Technology Department of Sichuan Province
2001
Laboratoire Magmas et Volcans
2001
Centre National de la Recherche Scientifique
2001
Université Clermont Auvergne
2001
New structural, petrographic, and 40 Ar/ 39 Ar data constrain the kinematics of ASRR (Ailao Shan‐Red River shear zone). In XueLong Shan (XLS), geochronological reveal Triassic, Early Tertiary, Oligo‐Miocene thermal events. The latter event (33–26 Ma) corresponds to cooling during left‐lateral shear. FanSiPan (FSP) range, thrusting SaPa nappe, linked deformation, FSP granite occurred at ≈35 Ma. Rapid resumed 25–29 Ma as a result uplift within transtensive ASRR. DayNuiConVoi (DNCV), foliation...
In the present study, Rotation Forest ensemble was integrated with different base classifiers to develop hybrid models namely based Support Vector Machines (RFSVM), Artificial Neural Networks (RFANN), Decision Trees (RFDT), and Naïve Bayes (RFNB) for landslide susceptibility modelling. The validity of these evaluated using statistical methods such as Root Mean Square Error (RMSE), Kappa index, accuracy, area under success rate predictive curves (AUC). Part prone Pithoragarh district,...
In this study, the main goal is to compare predictive capability of Support Vector Machines (SVM) with four Bayesian algorithms namely Naïve Bayes Tree (NBT), network (BN), (NB), Decision Table (DTNB) for identifying landslide susceptibility zones in Pauri Garhwal district (India). First, inventory map was built using 1295 historical data, then total sixteen influencing factors were selected and tested modelling. Performance model evaluated compared Statistical based index methods, Area...
Landslide is a natural hazard which causes huge loss of properties and human life in many places the world. Mapping landslide susceptibility an important task for preventing combating landslides problems. Main objective this study to use different artificial intelligence methods namely support vector machines (SVM), neural networks (ANN), logistic regression (LR), reduced error-pruning tree (REPT) development models mapping Muong Lay district Vietnam. In total data 217 locations area was...
The Hoang Sa islands, located in the northern part of East Vietnam Sea, lack information on geological structural boundaries. gravity data from global marine model were analyzed using enhanced total horizontal gradient methods to delineate structures that appear as lineaments transformed anomaly maps area. Before applying techniques their effectiveness was demonstrated by comparing them with results method for a synthetic model. Applying shows most identified islands are trending WSW-ENE,...
Groundwater is one of the most important sources fresh water all over world, especially in those countries where rainfall erratic, such as Vietnam. Nowadays, machine learning (ML) models are being used for assessment groundwater potential region. Credal decision trees (CDT) ML which has been studies. In present study, performance CDT improved using various ensemble frameworks Bagging, Dagging, Decorate, Multiboost, and Random SubSpace. Based on these methods, five hybrid models, namely BCDT,...
This study propose a new approach through which the landslide susceptibility in Quang Nam (Vietnam) will be estimated using best model among following algorithms: Decision Table (DT), Naïve Bayes (NB), - (DTNB), Bagging Ensemble, Cascade Generalization Dagging Decorate MultiBoost MultiScheme Real Ada Boost Rotation Forest Random Sub Space Ensemble. In this regard, map with 1130 landslide, was created and further partitioned into training (70%) testing (30%) locations. The correlation-based...
Groundwater is one of the major valuable water resources for use communities, agriculture, and industries. In present study, we have developed three novel hybrid artificial intelligence (AI) models which a combination modified RealAdaBoost (MRAB), bagging (BA), rotation forest (RF) ensembles with functional tree (FT) base classifier groundwater potential mapping (GPM) in basaltic terrain at DakLak province, Highland Centre, Vietnam. Based on literature survey, these proposed AI are new not...
With the rapid advancement of technology, monitoring forest cover changes has become increasingly quantifiable through various techniques and methods. In this study, we developed a procedure that utilizes Deep Neuron Network (DNN) model Geographic Information Systems (GIS) based on high-resolution imagery captured at different time points to create change maps in Nui Luot, Chuong My, Hanoi. Two RGB (Red-Green-Blue) spectral images were by Unmanned Aerial Vehicle (UAV) two (pre-scene...