Binh Thai Pham
YOU?
Author Swipe
View article: Prediction of Optimum Water Content of soil using advanced machine learning methods: A comparative study of RF, SVM, and ANN models
Prediction of Optimum Water Content of soil using advanced machine learning methods: A comparative study of RF, SVM, and ANN models Open
In construction, achieving adequate soil compaction is essential for ensuring the strength and stability of geotechnical structures, with Optimum Water Content (OWC) being a critical parameter. Traditional laboratory methods for determinin…
View article: The Fake-Busy and True-Idle Problems of Running Graph Applications on Chiplet-Based Multi-cores
The Fake-Busy and True-Idle Problems of Running Graph Applications on Chiplet-Based Multi-cores Open
The open-source and community-supported gem5 simulator is one of the most popular tools for computer architecture research. This simulation infrastructure allows researchers to model modern computer hardware at the cycle level, and it has …
View article: Hybrid Model of LightGBM Regression and Grid Search Optimization for the Estimation of Permanent Deformation of Asphalt Mixtures Pavements
Hybrid Model of LightGBM Regression and Grid Search Optimization for the Estimation of Permanent Deformation of Asphalt Mixtures Pavements Open
This study aimed to estimate the permanent deformation of Asphalt Mixtures (AMs) of pavements (Fn) utilizing a hybrid LGBM-GSO machine learning model, which combines Light Gradient-Boost Machine (LGBM) regression and Grid Search Optimizati…
View article: Engineering Evaluation of Freshwater Lake Coastal Sand Dunes: A Study of Sandbanks Provincial Park, Kingston, Canada
Engineering Evaluation of Freshwater Lake Coastal Sand Dunes: A Study of Sandbanks Provincial Park, Kingston, Canada Open
This study provides a comprehensive engineering evaluation of the freshwater coastal sand dunes at Sandbanks Provincial Park, located on the southern edge of Prince Edward County, Kingston, Ontario, Canada. Sandbanks is renowned for its ex…
View article: Investigation of the Gaussian Process with Various Kernel Functions for the Prediction of the Compressive Strength of Concrete
Investigation of the Gaussian Process with Various Kernel Functions for the Prediction of the Compressive Strength of Concrete Open
The Compressive Strength of Concrete (CSC) is a critical parameter for evaluating the quality of concrete used in various construction projects, including buildings, bridges, and roads. The primary objective of this study is to examine the…
View article: Geotechnical Challenges and Solutions in the Construction of Underground Powerhouse with Shallow Basalt Rock Cover: A Review of Sardar Sarovar Narmada Project Case Study
Geotechnical Challenges and Solutions in the Construction of Underground Powerhouse with Shallow Basalt Rock Cover: A Review of Sardar Sarovar Narmada Project Case Study Open
The Sardar Sarovar Narmada Project in Gujarat, India, provides a critical case study of underground powerhouse construction, completed in 2003, under challenging geological conditions, specifically with a shallow basalt rock cover. This pa…
View article: Novel Ensemble Models Based on the Split‐Point Sampling and Node Attribute Subsampling Classifier for Groundwater Potential Mapping
Novel Ensemble Models Based on the Split‐Point Sampling and Node Attribute Subsampling Classifier for Groundwater Potential Mapping Open
Groundwater potential maps are crucial tools for effectively managing water resources, particularly in agriculturally focused countries such as Vietnam. However, creating these maps is a challenging task that requires reliable data and met…
View article: Prediction of seepage flow through earthfill dams using machine learning models
Prediction of seepage flow through earthfill dams using machine learning models Open
In this study, three machine learning models, namely, the Multilayer Perceptron Neural Networks (MLPNN), the Generalized Regression Neural Networks (GRNN) and the Radial Basis Function Neural Networks (RBFNN) were used for predicting seepa…
View article: Geotechnical Evaluation of Basalt Rocks: A Review in the Context of the Construction of Civil Engineering Structures
Geotechnical Evaluation of Basalt Rocks: A Review in the Context of the Construction of Civil Engineering Structures Open
Basalt rocks are a common geological formation that plays a crucial role in various engineering applications, such as construction, infrastructure development, and geotechnical engineering. Understanding the physical and geotechnical prope…
View article: Mapping of soil erosion susceptibility using advanced machine learning models at Nghe An, Vietnam
Mapping of soil erosion susceptibility using advanced machine learning models at Nghe An, Vietnam Open
Soil Erosion Susceptibility Mapping (SESM) is one of the practical approaches for managing and mitigating soil erosion. This study applied four Machine Learning (ML) models, namely the Multilayer Perceptron (MLP) classifier, AdaBoost, Ridg…
View article: Estimation of recompression coefficient of soil using a hybrid ANFIS-PSO machine learning model
Estimation of recompression coefficient of soil using a hybrid ANFIS-PSO machine learning model Open
Recompression coefficient (Cr) is =an essential parameter utilized to predict consolidation settlement of over-consolidated soil. Thus, the main aim of this work was to estimate accurately the Cr, using a hybrid ANFIS-PSO Machine Learning …
View article: Modeling and Mapping of Flood Susceptibility at Que Son District, Quang Nam Province, Vietnam using CatBoost
Modeling and Mapping of Flood Susceptibility at Que Son District, Quang Nam Province, Vietnam using CatBoost Open
In this research, the main objective is to model and map flood susceptibility in Que Son district, Quang Nam province, Vietnam using one of the effective machine learning model namely CatBoost. With this purpose, a total of 96 flood and no…
View article: Landslide susceptibility modeling and mapping at Dien Bien province, Vietnam using Bagging based MLP neural network
Landslide susceptibility modeling and mapping at Dien Bien province, Vietnam using Bagging based MLP neural network Open
In this article, the main aim is to build landslide susceptibility map at the Dien Bien province (Vietnam) using a hybrid machine learning model including BG-MLP which is a hybridization of Bagging and Multilayer Perceptron (MLP) neural ne…
View article: Using GA-ANFIS machine learning model for forecasting the load bearing capacity of driven piles
Using GA-ANFIS machine learning model for forecasting the load bearing capacity of driven piles Open
This paper is aimed to apply hybrid machine learning model namely GA-ANFIS, which is a combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA), for the prediction of total bearing capability of driven piles.…
View article: A novel swarm intelligence optimized extreme learning machine for predicting soil shear strength: A case study at Hoa Vuong new urban project (Vietnam)
A novel swarm intelligence optimized extreme learning machine for predicting soil shear strength: A case study at Hoa Vuong new urban project (Vietnam) Open
In geotechnical engineering, soil shear strength is one of the most important parameters used in the design and construction of construction projects. However, determining this parameter in the laboratory is costly and time-consuming. Ther…
View article: Multiplex RT Real-Time PCR Based on Target Failure to Detect and Identify Different Variants of SARS-CoV-2: A Feasible Method That Can Be Applied in Clinical Laboratories
Multiplex RT Real-Time PCR Based on Target Failure to Detect and Identify Different Variants of SARS-CoV-2: A Feasible Method That Can Be Applied in Clinical Laboratories Open
Shortly after its emergence, Omicron and its sub-variants have quickly replaced the Delta variant during the current COVID-19 outbreaks in Vietnam and around the world. To enable the rapid and timely detection of existing and future varian…
View article: Forecasting Construction Price Index using Artificial Intelligence Models: Support Vector Machines and Radial Basis Function Neural Network
Forecasting Construction Price Index using Artificial Intelligence Models: Support Vector Machines and Radial Basis Function Neural Network Open
Estimation of Construction Price Index (CPI) is important for a market economy and it is a measure to manage construction investment costs. This is a tool to help organizations and individuals to reduce the effort and management of expense…
View article: Forecasting Construction Price Index using Artificial Intelligence Models: Support Vector Machines and Radial Basis Function Neural Network
Forecasting Construction Price Index using Artificial Intelligence Models: Support Vector Machines and Radial Basis Function Neural Network Open
Estimation of Construction Price Index (CPI) is important for a market economy and it is a measure to manage construction investment costs. This is a tool to help organizations and individuals to reduce the effort and management of expense…
View article: Forecasting Construction Price Index using Artificial Intelligence Models: Support Vector Machines and Radial Basis Function Neural Network
Forecasting Construction Price Index using Artificial Intelligence Models: Support Vector Machines and Radial Basis Function Neural Network Open
Estimation of Construction Price Index (CPI) is important for a market economy and it is a measure to manage construction investment costs. This is a tool to help organizations and individuals to reduce the effort and management of expense…
View article: Prediction of Flash Flood Susceptibility of Hilly Terrain Using Deep Neural Network: A Case Study of Vietnam
Prediction of Flash Flood Susceptibility of Hilly Terrain Using Deep Neural Network: A Case Study of Vietnam Open
Flash floods are one of the most dangerous natural disasters, especially in hilly terrain, causing loss of life, property, and infrastructures and sudden disruption of traffic. These types of floods are mostly associated with landslides an…
View article: Intergration of Rotation Forest and MultiBoost Ensembles with Forest by Penalizing Attributes for Spatial Prediction of Landslide Susceptibility
Intergration of Rotation Forest and MultiBoost Ensembles with Forest by Penalizing Attributes for Spatial Prediction of Landslide Susceptibility Open
Dien Bien province is considered one of the most prone to landslides areas of Vietnam. This study focused on developing landslide susceptibility maps (LSMs) for the study area using advanced machine learning prediction models, namely, Fore…
View article: New machine learning ensemble for flood susceptibility estimation
New machine learning ensemble for flood susceptibility estimation Open
Natural disasters in particular have resulted in several economic losses that are resulting from an exponential increase in the number of economic losses in general across the globe. The floods are among the most severe natural hazards phe…
View article: Hybrid Model: Teaching Learning-Based Optimization of Artificial Neural Network (TLBO-ANN) for the Prediction of Soil Permeability Coefficient
Hybrid Model: Teaching Learning-Based Optimization of Artificial Neural Network (TLBO-ANN) for the Prediction of Soil Permeability Coefficient Open
The permeability coefficient (k-value) of the soil is an important parameter used in the civil engineering design of roads, tunnels, dams, and other structures. However, the determination of k-value by experimental methods in the laborator…