Interpretable XGBoost-SHAP Machine-Learning Model for Shear Strength Prediction of Squat RC Walls

Modelling and interpreting pre-evacuation decision-making using machine learning

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

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Metaresearching Structural Engineering Using Text Mining: Trend Identifications and Knowledge Gap Discoveries

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

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

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Deep learning-based classification of earthquake-impacted buildings using textual damage descriptions

(2019) Sujith Mangalathu et al.   International Journal of Disaster Risk Reduction

Developing an XGBoost model to predict blast-induced peak particle velocity in an open-pit mine: a case study

(2019) Hoang Nguyen et al.   Acta Geophysica

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

(2019) Jalal Kiani et al.   COMPUTERS & STRUCTURES

Robust Pixel-Level Crack Detection Using Deep Fully Convolutional Neural Networks

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Machine Learning–Based Failure Mode Recognition of Circular Reinforced Concrete Bridge Columns: Comparative Study

(2019) Sujith Mangalathu et al.   JOURNAL OF STRUCTURAL ENGINEERING

Machine learning-based compressive strength prediction for concrete: An adaptive boosting approach

(2019) De-Cheng Feng et al.   CONSTRUCTION AND BUILDING MATERIALS

A metamodeling based seismic life-cycle cost assessment framework for highway bridge structures

(2019) Shivang Shekhar et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Machine learning algorithms for structural performance classifications and predictions: Application to reinforced masonry shear walls

(2019) Ahmad Siam et al.   Structures

Seismic fragility analysis with artificial neural networks: Application to nuclear power plant equipment

(2018) Zhiyi Wang et al.   ENGINEERING STRUCTURES

General solution for shear strength estimate of RC elements based on panel response

(2018) Leonardo M. Massone et al.   ENGINEERING STRUCTURES

XGBFEMF: An XGBoost-based Framework for Essential Protein Prediction

(2018) Jiancheng Zhong et al.   IEEE TRANSACTIONS ON NANOBIOSCIENCE

A Data-Driven Design for Fault Detection of Wind Turbines Using Random Forests and XGboost

(2018) Dahai Zhang et al.   IEEE Access

Explanation in artificial intelligence: Insights from the social sciences

(2018) Tim Miller   ARTIFICIAL INTELLIGENCE

Probabilistic development of shear strength model for reinforced concrete squat walls

(2016) Chao-Lie Ning et al.   EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS

Flange effects on seismic performance of reinforced concrete squat walls with irregular or regular openings

(2016) Bing Li et al.   ENGINEERING STRUCTURES

Shear strength of squat walls: A strut-and-tie model and closed-form design formula

(2015) Wael Kassem   ENGINEERING STRUCTURES

Experimental Evaluation of Seismic Performance of Squat RC Structural Walls with Limited Ductility Reinforcing Details

(2015) Bing Li et al.   JOURNAL OF EARTHQUAKE ENGINEERING

Seismic Performance Parameter Quantification of Shear-Critical Reinforced Concrete Masonry Squat Walls

(2013) Wael W. El-Dakhakhni et al.   JOURNAL OF STRUCTURAL ENGINEERING

Explaining prediction models and individual predictions with feature contributions

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Metamodel-based regional vulnerability estimate of irregular steel moment-frame structures subjected to earthquake events

(2012) Junwon Seo et al.   ENGINEERING STRUCTURES

Permutation importance: a corrected feature importance measure

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Strength prediction of squat structural walls via calibration of a shear–flexure interaction model

(2010) Leonardo M. Massone   ENGINEERING STRUCTURES