Influence of data splitting on performance of machine learning models in prediction of shear strength of soil
QH Nguyen, HB Ly, LS Ho, N Al-Ansari… - Mathematical …, 2021 - Wiley Online Library
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
Prediction of axial load capacity of rectangular concrete-filled steel tube columns using machine learning techniques
This work aims to develop a novel and practical equation for predicting the axial load of
rectangular concrete-filled steel tubular (CFST) columns based on soft computing …
rectangular concrete-filled steel tubular (CFST) columns based on soft computing …
Soft computing ensemble models based on logistic regression for groundwater potential mapping
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …
groundwater storage resources. In this study, we proposed four ensemble soft computing …
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 …
Evaluation of the ultimate eccentric load of rectangular CFSTs using advanced neural network modeling
In this paper an Artificial Neural Network (ANN) model is developed for the prediction of the
ultimate compressive load of rectangular Concrete Filled Steel Tube (CFST) columns, taking …
ultimate compressive load of rectangular Concrete Filled Steel Tube (CFST) columns, taking …
Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
F Bagherzadeh, AS Nouri, MJ Mehrani… - Process Safety and …, 2021 - Elsevier
Abstract Treatment of municipal wastewater to meet the stringent effluent quality standards is
an energy-intensive process and the main contributor to the costs of wastewater treatment …
an energy-intensive process and the main contributor to the costs of wastewater treatment …
Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models
HB Ly, BT Pham, LM Le, TT Le, VM Le… - Neural Computing and …, 2021 - Springer
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 …
Liquefaction prediction with robust machine learning algorithms (SVM, RF, and XGBoost) supported by genetic algorithm-based feature selection and parameter …
Liquefaction prediction is an important issue in the seismic design of engineering structures,
and research on this topic has been continuing in current literature using different methods …
and research on this topic has been continuing in current literature using different methods …
Practical machine learning-based prediction model for axial capacity of square CFST columns
TT Le - Mechanics of Advanced Materials and Structures, 2022 - Taylor & Francis
In this paper, a surrogate Machine-Learning (ML) model based on Gaussian Process
Regression (GPR) was developed to predict the axial load of square concrete-filled steel …
Regression (GPR) was developed to predict the axial load of square concrete-filled steel …