Machine-learning interpretability techniques for seismic performance assessment of infrastructure systems

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

(2020) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

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

Shear Strength of Internal Reinforced Concrete Beam-Column Joints: Intelligent Modeling Approach and Sensitivity Analysis

(2020) De-Cheng Feng et al.   Advances in Civil Engineering

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

(2020) Jalal Kiani et al.   COMPUTERS & STRUCTURES

Failure risk analysis of pipelines using data-driven machine learning algorithms

(2020) Ram K. Mazumder et al.   STRUCTURAL SAFETY

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

(2019) Jalal Kiani et al.   COMPUTERS & STRUCTURES

Stripe‐based fragility analysis of multispan concrete bridge classes using machine learning techniques

(2019) Sujith Mangalathu et al.   EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS

Classifying Earthquake Damage to Buildings Using Machine Learning

(2019) Sujith Mangalathu et al.   EARTHQUAKE SPECTRA

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

(2019) Mohamad Alipour et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

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

Rapid seismic damage evaluation of bridge portfolios using machine learning techniques

(2019) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

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

(2019) Ahmad Siam et al.   Structures

Classification of failure mode and prediction of shear strength for reinforced concrete beam-column joints using machine learning techniques

(2018) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Artificial neural network based multi-dimensional fragility development of skewed concrete bridge classes

(2018) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Enhanced fragility analysis of buried pipelines through Lasso regression

(2018) Pengpeng Ni et al.   Acta Geotechnica

Identification of the significant uncertain parameters in the seismic response of irregular bridges

(2017) Farahnaz Soleimani et al.   ENGINEERING STRUCTURES

Strength, deformation capacity and failure modes of RC walls under cyclic loading

(2015) Sofia Grammatikou et al.   Bulletin of Earthquake Engineering

Statistical models for shear strength of RC beam-column joints using machine-learning techniques

(2014) Jong-Su Jeon et al.   EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS

Use of response surface metamodels to generate system level fragilities for existing curved steel bridges

(2013) Junwon Seo et al.   ENGINEERING STRUCTURES

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

(2012) Junwon Seo et al.   ENGINEERING STRUCTURES

OpenSees: A Framework for Earthquake Engineering Simulation

(2011) Frank McKenna   COMPUTING IN SCIENCE & ENGINEERING

Seismic Performance of Sacrificial Exterior Shear Keys in Bridge Abutments

(2009) Pedro F. Silva et al.   EARTHQUAKE SPECTRA

Validated Simulation Models for Lateral Response of Bridge Abutments with Typical Backfills

(2009) Anoosh Shamsabadi et al.   Journal of Bridge Engineering