Plastic hinge length of rectangular RC columns using ensemble machine learning model

A predictive model for the bond strength of near-surface-mounted FRP bonded to concrete

(2021) Ruiliang Zhang et al.   COMPOSITE STRUCTURES

Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements

(2021) De-Cheng Feng et al.   ENGINEERING STRUCTURES

Development of extreme gradient boosting model for prediction of punching shear resistance of r/c interior slabs

(2021) Hoang D. Nguyen et al.   ENGINEERING STRUCTURES

Data-driven shear strength prediction of steel fiber reinforced concrete beams using machine learning approach

(2021) Jesika Rahman et al.   ENGINEERING STRUCTURES

Gradient Boosting Coupled with Oversampling Model for Prediction of Concrete Pipe-Joint Infiltration Using Designwise Data Set

(2021) Lui S. Wong et al.   Journal of Pipeline Systems Engineering and Practice

Data-driven machine-learning-based seismic failure mode identification of reinforced concrete shear walls

(2020) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Failure mode classification and bearing capacity prediction for reinforced concrete columns based on ensemble machine learning algorithm

(2020) De-Cheng Feng et al.   ADVANCED ENGINEERING INFORMATICS

Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach

(2020) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Application of pool-based active learning in reducing the number of required response history analyses

(2020) Jalal Kiani et al.   COMPUTERS & STRUCTURES

Machine learning prediction of compressive strength for phase change materials integrated cementitious composites

(2020) Afshin Marani et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning-based prediction of CFST columns using gradient tree boosting algorithm

(2020) Quang-Viet Vu et al.   COMPOSITE STRUCTURES

Prediction model of the failure mode of beam-column joints using machine learning methods

(2020) Xiangling Gao et al.   ENGINEERING FAILURE ANALYSIS

Data-Driven Approach to Predict the Plastic Hinge Length of Reinforced Concrete Columns and Its Application

(2020) De-Cheng Feng et al.   JOURNAL OF STRUCTURAL ENGINEERING

On the application of machine learning techniques to derive seismic fragility curves

(2019) Jalal Kiani et al.   COMPUTERS & STRUCTURES

Emerging artificial intelligence methods in structural engineering

(2018) Hadi Salehi et al.   ENGINEERING STRUCTURES

A machine learning framework for assessing post-earthquake structural safety

(2018) Yu Zhang et al.   STRUCTURAL SAFETY

Evaluation of the critical plastic region length in slender reinforced concrete bridge columns

(2016) Ata Babazadeh et al.   ENGINEERING STRUCTURES

Plastic hinge length of shape memory alloy (SMA) reinforced concrete bridge pier

(2016) A.H.M. Muntasir Billah et al.   ENGINEERING STRUCTURES

Probabilistic Approach for Estimating Plastic Hinge Length of Reinforced Concrete Columns

(2016) Chao-Lie Ning et al.   JOURNAL OF STRUCTURAL ENGINEERING

Probabilistic Approach for Estimating Plastic Hinge Length of Reinforced Concrete Columns

(2016) Chao-Lie Ning et al.   JOURNAL OF STRUCTURAL ENGINEERING

Displacement and plastic hinge length of FRP-confined circular reinforced concrete columns

(2015) Osama Youssf et al.   ENGINEERING STRUCTURES

Stacked Extreme Learning Machines

(2015) Hongming Zhou et al.   IEEE Transactions on Cybernetics

Analytical Study on Plastic Hinge Length of Structural Walls

(2012) İlker Kazaz   JOURNAL OF STRUCTURAL ENGINEERING

Experimental tests of slender reinforced concrete columns under combined axial load and lateral force

(2011) A.C. Barrera et al.   ENGINEERING STRUCTURES

Flexure-controlled ultimate deformations of members with continuous or lap-spliced bars

(2010) Dionysis Biskinis et al.   Structural Concrete

Towards the next generation of artificial neural networks for civil engineering

(2008) Ian Flood   ADVANCED ENGINEERING INFORMATICS