V. Tran

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Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression

Binh Thai Pham, Tien-Thinh Le, Hai-Bang Ly, 2020, Materials.

Prediction of Later-Age Concrete Compressive Strength Using Feedforward Neural Network

Hai-Van Thi Mai, H. Ly, V. Tran, 2020 .

Modelisation of chloride reactive transport in concrete including thermodynamic equilibrium, kinetic control and surface complexation

V. Tran, V. Baroghel-Bouny, A. Soive, 2018, Cement and Concrete Research.

Parametric Investigation of Particle Swarm Optimization to Improve the Performance of the Adaptive Neuro-Fuzzy Inference System in Determining the Buckling Capacity of Circular Opening Steel Beams

B. Pham, H. Ly, Tien-Thinh Le, 2020, Materials.

External sulfate attack of cementitious materials: New insights gained through numerical modeling including dissolution/precipitation kinetics and surface complexation

V. Tran, A. Soive, 2017 .

Laminar flow structure in vertical free convective cavities

G. Morrison, V. Tran, 1978 .

The advantages of using a geochemical transport model including thermodynamic equilibrium, kinetic control and surface complexation to simulate the durability of concretes exposed to chlorides and sulphates

M. Gasc-Barbier, V. Tran, A. Soive, 2019 .

Using hybrid machine learning model including gradient boosting and Bayesian optimization for predicting compressive strength of concrete containing ground glass particles

V. Tran, Linh Quy Nguyen, L. Nguyen, 2022, J. Intell. Fuzzy Syst..

Investigation of ANN architecture for predicting residual strength of clay soil

Lanh Si Ho, V. Tran, Hai Quan Do, 2022, Neural Computing and Applications.

Machine learning approach for predicting and evaluating California bearing ratio of stabilized soil containing industrial waste

Lanh Si Ho, V. Tran, 2022, Journal of Cleaner Production.

Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees and optimization algorithms

H. Ly, V. Tran, Thuy-Anh Nguyen, 2022, Frontiers of Structural and Civil Engineering.

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

Hai-Van Thi Mai, H. Ly, V. Tran, 2022, Frontiers of Structural and Civil Engineering.

Effect of temperature on the chloride binding capacity of cementitious materials

H. Ly, Tien-Thinh Le, V. Tran, 2021, Magazine of Concrete Research.

Nonlinear Analysis of Flat Steel Frame Semi rigid Connection Subjected to Dynamic Loads

H. Nguyen, V. Tran, T. Pham, 2019, VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE.

Novel hybrid machine learning models including support vector machine with meta-heuristic algorithms in predicting unconfined compressive strength of organic soils stabilised with cement and lime

V. Tran, T. Q. Ngo, L. Nguyen, 2022, International Journal of Pavement Engineering.

A numerical model including thermodynamic equilibrium, kinetic control and surface complexation in order to explain cation type effect on chloride binding capability of concrete

S. Bonnet, V. Tran, A. Khelidj, 2018, Construction and Building Materials.

Machine learning approach in investigating carbonation depth of concrete containing Fly ash

Hai-Van Thi Mai, M. H. Nguyen, V. Tran, 2022, Structural Concrete.

Using Artificial Intelligence Approach for Investigating and Predicting Yield Stress of Cemented Paste Backfill

V. Tran, 2023, Sustainability.

Predicting and Investigating the Permeability Coefficient of Soil with Aided Single Machine Learning Algorithm

V. Tran, 2022, Complex..

Hybrid gradient boosting with meta-heuristic algorithms prediction of unconfined compressive strength of stabilized soil based on initial soil properties, mix design and effective compaction

V. Tran, 2022, Journal of Cleaner Production.

Using machine learning technique for designing reinforced lightweight soil

V. Tran, L. Nguyen, 2022, J. Intell. Fuzzy Syst..

Developing random forest hybridization models for estimating the axial bearing capacity of pile

V. Tran, T. Pham, 2022, PloS one.

Prediction Compressive Strength of Concrete Containing GGBFS using Random Forest Model

Hai-Bang Ly, Van Quan Tran, Thuy-Anh Nguyen, 2021, Advances in Civil Engineering.

Investigation of ANN architecture for predicting shear strength of fiber reinforcement bars concrete beams

Long Khanh Nguyen, H. Ly, V. Tran, 2021, PloS one.

Compressive Strength Prediction of Stabilized Dredged Sediments Using Artificial Neural Network

V. Tran, 2021 .

Design deep neural network architecture using a genetic algorithm for estimation of pile bearing capacity

Hai-Bang Ly, Tuan Anh Pham, Van Quan Tran, 2020, PloS one.

A Novel Hybrid Model Based on a Feedforward Neural Network and One Step Secant Algorithm for Prediction of Load-Bearing Capacity of Rectangular Concrete-Filled Steel Tube Columns

Tien-Thinh Le, Hai-Bang Ly, Van Quan Tran, 2020, Molecules.

Application of machine learning technique for predicting and evaluating chloride ingress in concrete

Lanh Si Ho, V. Tran, R. George, 2022, Frontiers of Structural and Civil Engineering.

Influence of Data Splitting on Performance of Machine Learning Models in Prediction of Shear Strength of Soil

Nadhir Al-Ansari, Binh Thai Pham, Hai-Bang Ly, 2021 .

Using machine learning techniques for predicting autogenous shrinkage of concrete incorporating superabsorbent polymers and supplementary cementitious materials

V. Tran, B. Hilloulin, 2022, Journal of Building Engineering.

Development of deep neural network model to predict the compressive strength of rubber concrete

Hai-Bang Ly, Van Quan Tran, Thuy-Anh Nguyen, 2021 .

SIMULATION OF DETERIORATION PROCESS OF CONCRETE EXPOSED TO SULFURIC ACID

Hai-Van Thi Mai, V. Tran, 2020 .

Requirements and possible simplifications for multi-ionic transport models – Case of concrete subjected to wetting-drying cycles in marine environment

V. Tran, V. Baroghel-Bouny, A. Soive, 2018 .

Investigation of ANN Model Containing One Hidden Layer for Predicting Compressive Strength of Concrete with Blast-Furnace Slag and Fly Ash

Hai-Van Thi Mai, H. Ly, V. Tran, 2021 .

Simulation Of Chloride Ingress Into Unsaturated Concrete Exposed To Tidal Areas 1123

Huu Nam Nguyen, V. Tran, Q. Nguyen, 2019 .

Development of an AI Model to Measure Traffic Air Pollution from Multisensor and Weather Data

Binh Thai Pham, Tien-Thinh Le, Sybil Derrible, 2019, Sensors.

Development of Hybrid Machine Learning Models for Predicting the Critical Buckling Load of I-Shaped Cellular Beams

Vuong Minh Le, Lu Minh Le, Huong-Lan Thi Vu, 2019 .

Extreme Learning Machine Based Prediction of Soil Shear Strength: A Sensitivity Analysis Using Monte Carlo Simulations and Feature Backward Elimination

Nadhir Al-Ansari, Binh Thai Pham, Trung Nguyen-Thoi, 2020, Sustainability.

Multilingual Rules for Spam Detection

Frank Jiang, Quang Anh Tran, Minh Tuan Vu, 2015 .

Investigation of ANN Architecture for Predicting Load-Carrying Capacity of Castellated Steel Beams

Hai-Bang Ly, Van Quan Tran, Thuy-Anh Nguyen, 2021, Complex..

On the Training Algorithms for Artificial Neural Network in Predicting the Shear Strength of Deep Beams

Hai-Bang Ly, Van Quan Tran, Thuy-Anh Nguyen, 2021, Complex..

Using ANN to Estimate the Critical Buckling Load of Y Shaped Cross-Section Steel Columns

Hai-Bang Ly, Van Quan Tran, Thuy-Anh Nguyen, 2021, Sci. Program..

Estimation Of Compressive Strength Of Concrete Containing Manufactured Sand By Random Forest

H. Ly, V. Tran, 2020 .

Computational Hybrid Machine Learning Based Prediction of Shear Capacity for Steel Fiber Reinforced Concrete Beams

Binh Thai Pham, Tien-Thinh Le, Hai-Bang Ly, 2020, Sustainability.

Prediction of Pile Axial Bearing Capacity Using Artificial Neural Network and Random Forest

Hai-Bang Ly, Huong-Lan Thi Vu, Tuan Anh Pham, 2020 .

Investigation of ANN architecture for predicting the compressive strength of concrete containing GGBFS

Hai-Van Thi Mai, H. Ly, V. Tran, 2021, PloS one.

Investigation of Input Number Effect on Performance Prediction of Soil Friction Angle Using Random Forest

V. Tran, T. Pham, 2021, Lecture Notes in Civil Engineering.

Data-driven approach for investigating and predicting rutting depth of asphalt concrete containing reclaimed asphalt pavement

V. Tran, Hoang-Long Nguyen, 2023, Construction and Building Materials.

Developing interpretable machine learning-Shapley additive explanations model for unconfined compressive strength of cohesive soils stabilized with geopolymer

V. Tran, L. Nguyen, Anh Quan Ngo, 2023, PloS one.

Evolution of Deep Neural Network Architecture Using Particle Swarm Optimization to Improve the Performance in Determining the Friction Angle of Soil

Van Quan Tran, Tuan Anh Pham, Huong-Lan Thi Vu, 2021, Mathematical Problems in Engineering.

Selection of single machine learning model for designing compressive strength of stabilized soil containing lime, cement and bitumen

V. Tran, 2023, Journal of Intelligent & Fuzzy Systems.

Prediction of soil loss due to erosion using support vector machine model

Indra Prakash, V. Tran, 2020 .

Data‐driven approach for investigating and predicting of compressive strength of fly ash–slag geopolymer concrete

V. Tran, 2023, Structural Concrete.