Artificial intelligence-enabled smart mechanical metamaterials: advent and future trends
Mechanical metamaterials have opened an exciting venue for control and manipulation of
architected structures in recent years. Research in the area of mechanical metamaterials …
architected structures in recent years. Research in the area of mechanical metamaterials …
Development of deep neural network model to predict the compressive strength of rubber concrete
This paper presents an innovative development process of a Deep Neural Network model to
predict the compressive strength of rubber concrete. To this goal, a rubber concrete …
predict the compressive strength of rubber concrete. To this goal, a rubber concrete …
Development of advanced artificial intelligence models for daily rainfall prediction
In this study, the main objective is to develop and compare several advanced Artificial
Intelligent (AI) models namely Adaptive Network based Fuzzy Inference System optimized …
Intelligent (AI) models namely Adaptive Network based Fuzzy Inference System optimized …
Supervised machine learning techniques to the prediction of tunnel boring machine penetration rate
Predicting the penetration rate is a complex and challenging task due to the interaction
between the tunnel boring machine (TBM) and the rock mass. Many studies highlight the …
between the tunnel boring machine (TBM) and the rock mass. Many studies highlight the …
A sensitivity and robustness analysis of GPR and ANN for high-performance concrete compressive strength prediction using a Monte Carlo simulation
This study aims to analyze the sensitivity and robustness of two Artificial Intelligence (AI)
techniques, namely Gaussian Process Regression (GPR) with five different kernels …
techniques, namely Gaussian Process Regression (GPR) with five different kernels …
Metaheuristic optimization of Levenberg–Marquardt-based artificial neural network using particle swarm optimization for prediction of foamed concrete compressive …
Foamed concrete (FC) shows advantageous applications in civil engineering, such as
reduction in dead loads, contribution to energy conservation, or decrease the construction …
reduction in dead loads, contribution to energy conservation, or decrease the construction …
Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models
The main objective of the present work is to estimate the load-carrying capacity of concrete-
filled steel tubes (CFST) under axial compression using hybrid artificial intelligence (AI) …
filled steel tubes (CFST) under axial compression using hybrid artificial intelligence (AI) …
Groundwater potential mapping combining artificial neural network and real AdaBoost ensemble technique: the DakNong province case-study, Vietnam
The main aim of this study is to assess groundwater potential of the DakNong province,
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …
A comparative study of kernel logistic regression, radial basis function classifier, multinomial naïve bayes, and logistic model tree for flash flood susceptibility mapping
Risk of flash floods is currently an important problem in many parts of Vietnam. In this study,
we used four machine-learning methods, namely Kernel Logistic Regression (KLR), Radial …
we used four machine-learning methods, namely Kernel Logistic Regression (KLR), Radial …
Hybrid gradient boosting with meta-heuristic algorithms prediction of unconfined compressive strength of stabilized soil based on initial soil properties, mix design and …
VQ Tran - Journal of Cleaner Production, 2022 - Elsevier
In the investigation, hybrid Gradient Boosting (GB) with four optimization techniques named
Simulated Annealing (SA), Random Restart Hill Climbing (RRHC), Particle Swarm …
Simulated Annealing (SA), Random Restart Hill Climbing (RRHC), Particle Swarm …