On the public citation graph

An Inverse Bayesian Network Framework for Uncertainty Quantification in Bridge Influence Line Identification

https://doi.org/10.2139/ssrn.5072692
0 signed · 45 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/stc.2355openalex-snapshot
Bridge influence line identification based on adaptive B‐spline basis dictionary and sparse regularization
inferredcites →https://doi.org/10.1002/stc.2544openalex-snapshot
Bridge influence line identification from structural dynamic responses induced by a high‐speed vehicle
inferredcites →https://doi.org/10.1002/stc.3080openalex-snapshot
A statistical influence line identification method using Bayesian regularization and a polynomial interpolating function
inferredcites →https://doi.org/10.1007/978-981-97-2417-8_8openalex-snapshot
Quantifying Uncertainties in Model Updating Following Bayesian Approach Using a Parameter Space-Search Algorithm
inferredcites →https://doi.org/10.1007/s11831-026-10688-3openalex-snapshot
Navigating Uncertainties in Machine Learning for Structural Dynamics: A Comprehensive Survey of Probabilistic and Non-Probabilistic Approaches
inferredcites →https://doi.org/10.1016/j.cie.2024.110161openalex-snapshot
A Bayesian decision network–based pre-disaster mitigation model for earthquake-induced cascading events to balance costs and benefits on a limited budget
inferredcites →https://doi.org/10.1016/j.engappai.2019.103384openalex-snapshot
Uncertainties in conditional probability tables of discrete Bayesian Belief Networks: A comprehensive review
inferredcites →https://doi.org/10.1016/j.engstruct.2016.03.057openalex-snapshot
System reliability-based seismic collapse assessment of steel moment frames using incremental dynamic analysis and Bayesian probability network
inferredcites →https://doi.org/10.1016/j.engstruct.2016.08.029openalex-snapshot
Bayesian-network-based system identification of spatial distribution of structural parameters
inferredcites →https://doi.org/10.1016/j.engstruct.2017.06.067openalex-snapshot
Extraction of influence line through a fitting method from bridge dynamic response induced by a passing vehicle
inferredcites →https://doi.org/10.1016/j.engstruct.2019.109539openalex-snapshot
Development of bridge influence line identification methods based on direct measurement data: A comprehensive review and comparison
inferredcites →https://doi.org/10.1016/j.engstruct.2021.113166openalex-snapshot
Reliability-based vehicle weight limit determination for urban bridge network subjected to stochastic traffic flow considering vehicle-bridge coupling
inferredcites →https://doi.org/10.1016/j.engstruct.2024.118477openalex-snapshot
Bayesian time domain approach for damping identification and uncertainty quantification in stay cables using free vibration response
inferredcites →https://doi.org/10.1016/j.epsr.2024.110860openalex-snapshot
Bayesian Physics-informed Neural Networks for system identification of inverter-dominated power systems
inferredcites →https://doi.org/10.1016/j.ijthermalsci.2022.107837openalex-snapshot
A regularization method for inverse heat transfer problems using dynamic Bayesian networks with variable structure
inferredcites →https://doi.org/10.1016/j.ins.2022.01.020openalex-snapshot
Dynamic embeddings for efficient parameter learning of Bayesian network with multiple latent variables
inferredcites →https://doi.org/10.1016/j.istruc.2023.01.058openalex-snapshot
The effect of environmental temperature on influence line of concrete beam type bridge
inferredcites →https://doi.org/10.1016/j.jclepro.2023.137372openalex-snapshot
A new method for flood disaster resilience evaluation: A hidden markov model based on Bayesian belief network optimization
inferredcites →https://doi.org/10.1016/j.measurement.2021.109807openalex-snapshot
Bridge influence line identification based on big data and interval analysis with affine arithmetic
inferredcites →https://doi.org/10.1016/j.neucom.2023.126239openalex-snapshot
Bayesian network parameter learning using fuzzy constraints
inferredcites →https://doi.org/10.1016/j.scs.2024.105294openalex-snapshot
Integrated Bayesian Network and Strongest Path Method (BN-SPM) for effective multi-hazard risk assessment of interconnected infrastructure systems
inferredcites →https://doi.org/10.1016/j.ymssp.2017.10.006openalex-snapshot
Enhance GO methodology for reliability analysis of the closed-loop system using Cyclic Bayesian Networks
inferredcites →https://doi.org/10.1016/j.ymssp.2022.108840openalex-snapshot
Gradient-based optimization for spectral-based multiple-leak identification
inferredcites →https://doi.org/10.1016/j.ymssp.2022.109133openalex-snapshot
Monitoring gross vehicle weight with a probabilistic and influence line-free bridge weight-in-motion scheme based on a transmissibility-like index
inferredcites →https://doi.org/10.1016/j.ymssp.2022.109263openalex-snapshot
Newtonized orthogonal matching pursuit-based compressive spherical beamforming in spherical harmonic domain
inferredcites →https://doi.org/10.1016/j.ymssp.2022.109933openalex-snapshot
A hierarchical Bayesian framework embedded with an improved orthogonal series expansion for Gaussian processes and fields identification
inferredcites →https://doi.org/10.1016/j.ymssp.2023.110830openalex-snapshot
Active learning aided Bayesian nonparametric general regression for model updating using modal data
inferredcites →https://doi.org/10.1016/j.ymssp.2024.111622openalex-snapshot
A novel bridge influence line identification approach based on nonlinear frequency modulation signal reconstruction
inferredcites →https://doi.org/10.1061/(asce)be.1943-5592.0000681openalex-snapshot
Damage Detection in Long Suspension Bridges Using Stress Influence Lines
inferredcites →https://doi.org/10.1061/(asce)be.1943-5592.0000723openalex-snapshot
Multiscale Modeling and Model Updating of a Cable-Stayed Bridge. II: Model Updating Using Modal Frequencies and Influence Lines
inferredcites →https://doi.org/10.1061/(asce)be.1943-5592.0001458openalex-snapshot
Bridge Influence Line Identification Based on Regularized Least-Squares QR Decomposition Method
inferredcites →https://doi.org/10.1061/(asce)em.1943-7889.0000173openalex-snapshot
Bayesian Network Enhanced with Structural Reliability Methods: Methodology
inferredcites →https://doi.org/10.1061/jbenf2.beeng-6235openalex-snapshot
Identification of Influence Lines for Highway Bridges Using Bayesian Parametric Estimation Based on Computer Vision Measurements
inferredcites →https://doi.org/10.1109/tkde.2007.1073openalex-snapshot
Using Ranked Nodes to Model Qualitative Judgments in Bayesian Networks
inferredcites →https://doi.org/10.1109/tkde.2016.2535229openalex-snapshot
Improving Construction of Conditional Probability Tables for Ranked Nodes in Bayesian Networks
inferredcites →https://doi.org/10.1142/s0218213011000449openalex-snapshot
BAYESIAN NETWORK WITH INTERVAL PROBABILITY PARAMETERS
inferredcites →https://doi.org/10.1142/s021945541640023xopenalex-snapshot
Stress Influence Line Identification of Long Suspension Bridges Installed with Structural Health Monitoring Systems
inferredcites →https://doi.org/10.1177/1369433221992482openalex-snapshot
Damage quantification of beam structures using deflection influence line changes and sparse regularization
inferredcites →https://doi.org/10.1177/14759217241248570openalex-snapshot
Identification of bridge influence line and multiple-vehicle loads based on physics-informed neural networks
inferredcites →https://doi.org/10.1201/9780367803018openalex-snapshot
Risk Assessment and Decision Analysis with Bayesian Networks
inferredcites →https://doi.org/10.1201/b13102openalex-snapshot
Risk Assessment and Decision Analysis with Bayesian Networks
inferredcites →https://doi.org/10.12989/cac.2017.20.5.563openalex-snapshot
A systematic method from influence line identification todamage detection: Application to RC bridges
inferredcites →https://doi.org/10.1680/bren.2006.159.1.31openalex-snapshot
Calculating an influence line from direct measurements
inferredcites →https://doi.org/10.2139/ssrn.4420269openalex-snapshot
Learning Bayesian Network Parameters from Limited Data Integrating Entropy and Monotonicity
inferredcites →https://doi.org/10.2139/ssrn.4768225openalex-snapshot
Bayesian Physics-Informed Neural Networks for System Identification of Inverter-Dominated Power Systems
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.