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Interpretable Surrogate Models for Seismic Response Estimation of Urban Highway Bridges Supported by Post-Tensioned Rocking Piers

https://doi.org/10.2139/ssrn.5389983
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Parametric experimental investigation of unbonded post‐tensioned reinforced concrete bridge piers under cyclic loading
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Modeling of force-displacement behavior of post-tensioned self-centering concrete connections
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Seismic response prediction and variable importance analysis of extended pile-shaft-supported bridges against lateral spreading: Exploring optimized machine learning models
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A machine-learning-based model for predicting the effective stiffness of precast concrete columns
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Predicting the drift capacity of precast concrete columns using explainable machine learning approach
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Explainable machine learning models for probabilistic buckling stress prediction of steel shear panel dampers
inferredcites →https://doi.org/10.1016/j.engstruct.2023.117307openalex-snapshot
Bayesian-optimized interpretable surrogate model for seismic demand prediction of urban highway bridges
inferredcites →https://doi.org/10.1016/j.engstruct.2024.117690openalex-snapshot
Shaking table tests of seismic-resilient post-tensioned reinforced concrete bridge piers with enhanced bases
inferredcites →https://doi.org/10.1016/j.engstruct.2024.119162openalex-snapshot
Seismic response of rocking bridge systems under three-dimensional ground motions
inferredcites →https://doi.org/10.1016/j.engstruct.2025.121061openalex-snapshot
Multi-objective seismic design optimization of self-centering bridges with novel mechanical hinges
inferredcites →https://doi.org/10.1016/j.istruc.2021.03.099openalex-snapshot
Quasi-static and nonlinear time-history analyses of post-tensioned bridge rocking piers with internal ED bars
inferredcites →https://doi.org/10.1016/j.istruc.2022.08.023openalex-snapshot
Explainable machine learning based efficient prediction tool for lateral cyclic response of post-tensioned base rocking steel bridge piers
inferredcites →https://doi.org/10.1016/j.istruc.2023.02.105openalex-snapshot
Application of machine learning in seismic fragility assessment of bridges with SMA-restrained rocking columns
inferredcites →https://doi.org/10.1016/j.istruc.2023.105089openalex-snapshot
Optimal combinations of parameters for seismic response prediction of high-speed railway bridges using machine learnings
inferredcites →https://doi.org/10.1016/j.jclepro.2023.138673openalex-snapshot
Machine learning models for predicting compressive strength of fiber-reinforced concrete containing waste rubber and recycled aggregate
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State-of-the-art AI-based computational analysis in civil engineering
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A measure of earthquake motion capacity to damage medium-period structures
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Induction of Decision Trees
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Seismic Damage Analysis of Reinforced Concrete Buildings
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Design, Modeling, and Experimental Response of Seismic Resistant Bridge Piers with Posttensioned Dissipating Connections
inferredcites →https://doi.org/10.1061/(asce)be.1943-5592.0000252openalex-snapshot
Behavior of Segmental Precast Posttensioned Bridge Piers under Lateral Loads
inferredcites →https://doi.org/10.1061/(asce)be.1943-5592.0001620openalex-snapshot
State-of-the-Art Review of Seismic-Resistant Precast Bridge Columns
inferredcites →https://doi.org/10.1061/(asce)be.1943-5592.0001833openalex-snapshot
State-of-the-Art of Posttensioned Rocking Bridge Substructure Systems
inferredcites →https://doi.org/10.1061/(asce)be.1943-5592.0001961openalex-snapshot
Seismic Performance of Self-Centering Bridge Piers with Rocking Mechanical Hinges
inferredcites →https://doi.org/10.1061/(asce)st.1943-541x.0001054openalex-snapshot
Seismic Behavior of Posttensioned Self-Centering Precast Concrete Dual-Shell Steel Columns
inferredcites →https://doi.org/10.1061/(asce)st.1943-541x.0001972openalex-snapshot
Seismic-Resistant Precast Concrete Structures: State of the Art
inferredcites →https://doi.org/10.1061/(asce)st.1943-541x.0003115openalex-snapshot
Interpretable XGBoost-SHAP Machine-Learning Model for Shear Strength Prediction of Squat RC Walls
inferredcites →https://doi.org/10.1061/(asce)st.1943-541x.0003392openalex-snapshot
Machine Learning for Risk and Resilience Assessment in Structural Engineering: Progress and Future Trends
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Quantifying Easy-to-Repair Displacement Ductility and Lateral Strength of Scoured Bridge Pile Group Foundations in Cohesionless Soils: A Classification–Regression Combination Surrogate Model
inferredcites →https://doi.org/10.1061/jmcea3.0000102openalex-snapshot
Behavior of Structures During Earthquakes
inferredcites →https://doi.org/10.1061/nhrefo.nheng-1837openalex-snapshot
Explainable XGBoost–SHAP Machine-Learning Model for Prediction of Ground Motion Duration in New Zealand
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Applied Statistics and Probability for Engineers
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Large Sample Properties of Simulations Using Latin Hypercube Sampling
inferredcites →https://doi.org/10.1080/13632460309350474openalex-snapshot
PROBABILISTIC SEISMIC DEMAND MODELS AND FRAGILITY ESTIMATES FOR RC BRIDGES
inferredcites →https://doi.org/10.1080/13632469.2023.2166163openalex-snapshot
Self-Centering Structures Against Earthquakes: A Critical Review
inferredcites →https://doi.org/10.1080/13632469909350343openalex-snapshot
THE EFFECTIVE DURATION OF EARTHQUAKE STRONG MOTION
inferredcites →https://doi.org/10.1109/icdar.1995.598994openalex-snapshot
Random decision forests
inferredcites →https://doi.org/10.1109/tnn.2005.845550openalex-snapshot
Neural Networks and Intellect: Using Model-Based Concepts
inferredcites →https://doi.org/10.1111/mice.13112openalex-snapshot
Machine learning–assisted drift capacity prediction models for reinforced concrete columns with shape memory alloy bars
inferredcites →https://doi.org/10.1145/2939672.2939785openalex-snapshot
XGBoost
inferredcites →https://doi.org/10.1177/1687814016633411openalex-snapshot
Modeling seismic performance of high-strength steel–ultra-high-performance concrete piers with modified Kent–Park model using fiber elements
inferredcites →https://doi.org/10.1177/8755293020919419openalex-snapshot
The promise of implementing machine learning in earthquake engineering: A state‐of‐the‐art review
inferredcites →https://doi.org/10.1177/87552930241290487openalex-snapshot
Component Restoration Models of Highway Bridges for Resilience Assessment: A Nationwide Expert‐Opinion Survey Study and Application
inferredcites →https://doi.org/10.1186/s43251-022-00058-xopenalex-snapshot
State-of-the-art review of the seismic performance of precast segmental columns
inferredcites →https://doi.org/10.1260/1369-4332.16.5.805openalex-snapshot
Simplified Analytical Pushover Method for Precast Segmental Concrete Bridge Columns
inferredcites →https://doi.org/10.14359/12296openalex-snapshot
Bond-Slip Response of Reinforcing Bars Grouted in Ducts
inferredcites →https://doi.org/10.3390/buildings14061833openalex-snapshot
Numerical Investigation of the Seismic-Induced Rocking Behavior of Unbonded Post-Tensioned Bridge Piers
inferredcites →https://doi.org/10.3390/infrastructures7050064openalex-snapshot
State-of-the-Art Review on Probabilistic Seismic Demand Models of Bridges: Machine-Learning Application
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On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)
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