Experimental validation of FE model updating based on multi-objective optimization using the surrogate model
활용도 Analysis
논문 Analysis
연구자 Analysis
저자
황용문
진승섭
정호연
김세훈
이종재
정형조
제어번호
105036621
학술지명
Structural Engineering and Mechanics, An Int'l Journal
권호사항
Vol.
65
No.
2
[
2018
]
발행처
국제구조공학회
자료유형
학술저널
수록면
173-181
언어
English
출판년도
2018
등재정보
SCIE;SCOPUS
판매처
'
Experimental validation of FE model updating based on multi-objective optimization using the surrogate model' 의 참고문헌
Structural identification with systematic errors and unknown uncertainty dependencies
Sequential surrogate modeling for efficient finite element model updating
Quantifying the effects of modeling simplifications for structural identification of bridges
Quantification of parametric model uncertainties in finite element model updating problem via fuzzy numbers
Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach
Multi-criteria Optimization Using the AMALGAM Software Package: Theory, Concepts, and MATLAB Implementation
Investigation of the effect of model uncertainties on structural response using structural health monitoring data
Introduction to Evolutionary Multiobjective Optimization
Improved evolutionary optimization from genetically adaptive multimethod search
Finite element model updating using response surface method
Finite element model updating taking into account the uncertainty on the modal parameters estimates
Finite element model updating in structural dynamics by using the response surface method
Engineering Design via Surrogate Modeling: A Practical Guide
Effect of secondary elements on bridge structural system reliability considering moment capacity
Committee on Structural Identification of Constructed Systems, Structural Identification of Constructed Systems: Approaches, Methods, and Technologies for Effective Practice of St-Id
Civil structure condition assessment by FE model updating: Methodology and case studies
Bayesian calibration of computer models
An improved updating parameter selection method and finite element model update using multi-objective optimization technique
Adaptive simulated annealing genetic algorithm for system identification
A taxonomy of global optimization methods based on response surfaces
A new multi-objective approach to finite element model updating
A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-2
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Experimental validation of FE model updating based on multi-objective optimization using the surrogate model'
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