A5027233897- Flood Risk Assessment and Management
- Landslides and related hazards
- Hydrology and Watershed Management Studies
- Groundwater and Watershed Analysis
- Fire effects on ecosystems
- Dam Engineering and Safety
- Geotechnical Engineering and Analysis
- Hydrological Forecasting Using AI
- Soil and Unsaturated Flow
- Grouting, Rheology, and Soil Mechanics
- Hydrology and Drought Analysis
- Infrastructure Maintenance and Monitoring
- Cryospheric studies and observations
- Soil erosion and sediment transport
- Tree Root and Stability Studies
- Poverty, Education, and Child Welfare
- Asphalt Pavement Performance Evaluation
- International Development and Aid
- Adsorption and biosorption for pollutant removal
- Structural Health Monitoring Techniques
- Drilling and Well Engineering
- Gender, Education, and Development Issues
- Mineral Processing and Grinding
- Transport Systems and Technology
- Grey System Theory Applications
University Of Transport Technology
2019-2025
Duy Tan University
2020-2021
Ho Chi Minh City International University
2016
Ho Chi Minh City University of Technology
2016
Vietnam National University Ho Chi Minh City
2016
The main objective of this study is to evaluate and compare the performance different machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Boosting Trees (Boosted) considering influence various training testing ratios in predicting soil shear strength, one most critical geotechnical engineering properties civil design construction. For aim, a database 538 samples collected from Long Phu 1 power plant project, Vietnam, was utilized...
Predicting and mapping fire susceptibility is a top research priority in fire-prone forests worldwide. This study evaluates the abilities of Bayes Network (BN), Naïve (NB), Decision Tree (DT), Multivariate Logistic Regression (MLP) machine learning methods for prediction across Pu Mat National Park, Nghe An Province, Vietnam. The modeling methodology was formulated based on processing information from 57 historical fires set nine spatially explicit explanatory variables, namely elevation,...
Flash floods are one of the most devastating natural hazards; they occur within a catchment (region) where response time drainage basin is short. Identification probable flash flood locations and development accurate susceptibility maps important for proper management region. With this objective, we proposed compared several novel hybrid computational approaches machine learning methods mapping, namely AdaBoostM1 based Credal Decision Tree (ABM-CDT); Bagging (Bag-CDT); Dagging (Dag-CDT);...
Groundwater potential maps are one of the most important tools for management groundwater storage resources. In this study, we proposed four ensemble soft computing models based on logistic regression (LR) combined with dagging (DLR), bagging (BLR), random subspace (RSSLR), and cascade generalization (CGLR) techniques mapping in Dak Lak Province, Vietnam. A suite well yield data twelve geo-environmental factors (aspect, elevation, slope, curvature, Sediment Transport Index, Topographic...
: The main aim of this study is to assess groundwater potential the DakNong province, Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates Artificial Neural Networks (ANN) with RealAdaBoost (RAB) technique. For study, twelve conditioning factors and wells yield data was used create training testing datasets for development validation RABANN model. Area Under Receiver Operating Characteristic (ROC) curve (AUC) several statistical performance measures were...
Determination of shear strength soil is very important in civil engineering for foundation design, earth and rock fill dam highway airfield stability slopes cuts, the design coastal structures. In this study, a novel hybrid soft computing model (RF-PSO) random forest (RF) particle swarm optimization (PSO) was developed used to estimate undrained based on clay content (%), moisture specific gravity void ratio liquid limit plastic (%). experimental results 127 samples from national project Hai...
Improving the accuracy of flood prediction and mapping is crucial for reducing damage resulting from events. In this study, we proposed validated three ensemble models based on Best First Decision Tree (BFT) Bagging (Bagging-BFT), Decorate Random Subspace (RSS-BFT) learning techniques an improved susceptibility in a spatially-explicit manner. A total number 126 historical events Nghe An Province (Vietnam) were connected to set 10 influencing factors (slope, elevation, aspect, curvature,...
In this study, we have developed five spatially explicit ensemble predictive machine learning models for the landslide susceptibility mapping of Van Chan district Yen Bai Province, Vietnam. model studies, Random Subspace (RSS) was used as learner with Best First Decision Tree (BFT), Functional (FT), J48 (J48DT), Naïve Bayes (NBT) and Reduced Error Pruning Trees (REPT) base classifiers. Data 167 past present landslides various conditioning factors were generation datasets. The results showed...
The Yamuna river has become one of the most polluted rivers in India as well world because high-density population growth and speedy industrialization. is severely needs urgent revival. Dehradun due to exceptional tourist activity, poor sewage facilities, insufficient wastewater management amenities. measurement quality can be done by water assessment. In this study, index been calculated for at using monthly measurements 12 physicochemical parameters. Trend forecasting pollution performed...
In this study, we have investigated rainfall induced landslide susceptibility of the Uttarkashi district India through developmentof different novel GIS based soft computing approaches namely Bagging-MLPC, Dagging-MLPC, Decorate-MLPC which are a combination Multi-layer Perceptron Neural Network Classifier (MLPC) and Bagging, Dagging, Decorate ensemble methods, respectively. The proposed models were trained validated with help 103 historical events (divided into 2 samples: training (70%)...
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,...
In this paper, we developed highly accurate ensemble machine learning models integrating Reduced Error Pruning Tree (REPT) as a base classifier with the Bagging (B), Decorate (D), and Random Subspace (RSS) techniques for spatial prediction of rainfall-induced landslides in Uttarkashi district, located Himalayan range, India. To do so, total 103 historical landslide events were linked to twelve conditioning factors generating training validation datasets. Root Mean Square (RMSE) Area Under...
Development of landslide predictive models with strong prediction power has become a major focus many researchers. This study describes the first application Hyperpipes (HP) algorithm for development five novel ensemble that combine HP and AdaBoost (AB), Bagging (B), Dagging, Decorate, Real (RAB) techniques mapping spatial variability susceptibility in Nam Dan commune, Ha Giang province, Vietnam. Information on 76 historical landslides ten geo-environmental factors (slope degree, slope...
Abstract Introduction The Human Development Index (HDI), as one of the more complex composite indicators level human potential and quality life, is a combination three dimensions (indicators, factors): life expectancy at birth, middle number years education expected schooling combined into single index economic benefits expressed by production, or GDP (gross domestic product) according to purchasing power (PPP US $). Methods same measures average achievements in field health, education,...
Vietnam has been extensively affected by floods, suffering heavy losses in human life and property. While the Vietnamese government focused on structural measures of flood defence such as levees early warning systems, country still lacks risk assessment methodologies frameworks at local national levels. In response to this gap, study developed a framework that uses historical mark data high-resolution digital elevation model create an inundation map, then combined map with exposure...