Ensemble learning based hierarchical surrogate model for multi-fidelity information fusion
Recently, multi-fidelity information fusion based surrogate modeling methods have made
great progress in the engineering design and optimization tasks. Two main issues in this …
great progress in the engineering design and optimization tasks. Two main issues in this …
A multi-fidelity Bayesian optimization approach for constrained multi-objective optimization problems
In this paper, a multi-fidelity Bayesian optimization approach is presented to tackle
computationally expensive constrained multiobjective optimization problems (MOPs). The …
computationally expensive constrained multiobjective optimization problems (MOPs). The …
A systematic framework of constructing surrogate model for slider track peeling strength prediction
XJ Dong, Q Chen, WB Liu, D Wang, ZK Peng… - Science China …, 2024 - Springer
Peeling strength can comprehensively reflect slider track safety and is crucial in car seat
safety assessments. Current methods for determining slider peeling strength are primarily …
safety assessments. Current methods for determining slider peeling strength are primarily …
A novel multi-fidelity modeling method with double adaptive selection of kernel and learning functions—Application to spaceborne deployable antennas
The multi-fidelity surrogate (MFS) model that integrates high-fidelity and low-fidelity data is a
promising and powerful tool for tackling complex modeling problem. There are two essential …
promising and powerful tool for tackling complex modeling problem. There are two essential …
Online multi-fidelity data aggregation via hierarchical neural network
C Hai, J Wang, S Guo, W Qian, L Mei - Computer Methods in Applied …, 2025 - Elsevier
In many industrial applications requiring computational modeling, the acquisition of high-
fidelity data is often constrained by cost and technical limitations, while low-fidelity data …
fidelity data is often constrained by cost and technical limitations, while low-fidelity data …
A comprehensive multi-fidelity surrogate framework based on Gaussian process for datasets with heterogeneous responses
In recent decades, the multi-fidelity (MF) surrogate framework has seen widespread
application across various scenarios. This framework significantly enhances the efficiency of …
application across various scenarios. This framework significantly enhances the efficiency of …
Generative adversarial networks for multi-fidelity matrix completion with massive missing entries
Multi-fidelity matrices refer to a pair of data matrices, whose entries are the measurements of
a specific physical quantity at different fidelity levels wrt two environment variables arranged …
a specific physical quantity at different fidelity levels wrt two environment variables arranged …
Bi-fidelity surrogate modeling via scaled correlation construction and penalty minimization
Bi-fidelity surrogate (BFS) modeling is a powerful technique to mitigate the constraints of
computational time and resources in high-fidelity (HF) models. However, obtaining sufficient …
computational time and resources in high-fidelity (HF) models. However, obtaining sufficient …