Few-shot structural repair decision of civil aircraft based on deep meta-learning
C Che, H Wang, X Ni, M Xiong - Engineering Applications of Artificial …, 2023 - Elsevier
To solve the difficulties in extracting general features of few-shot high-dimensional structural
health monitoring data and making accurate repair decision, a civil aircraft structural repair …
health monitoring data and making accurate repair decision, a civil aircraft structural repair …
Few-shot fault diagnosis of rolling bearing under variable working conditions based on ensemble meta-learning
C Che, H Wang, M Xiong, X Ni - Digital Signal Processing, 2022 - Elsevier
Accurate fault diagnosis of rolling bearing under variable working conditions can ensure that
the rotating machinery run in a safety, reliable and efficient way. In this paper, we propose …
the rotating machinery run in a safety, reliable and efficient way. In this paper, we propose …
A reanalysis-based multi-fidelity (RBMF) surrogate framework for efficient structural optimization
In recent years, research on multi-fidelity (MF) surrogate modeling, which integrates high-
fidelity (HF) and low-fidelity (LF) models, has been conducted to improve efficiency in …
fidelity (HF) and low-fidelity (LF) models, has been conducted to improve efficiency in …
Nominal digital twin for new-generation product design
With the increasing competition of the manufacturing industry, it is essential for
manufacturers to develop a new (or next)-generation product based on their prior product …
manufacturers to develop a new (or next)-generation product based on their prior product …
Efficient scenario analysis for optimal adaptation of bridge networks under deep uncertainties through knowledge transfer
M Cheng, DM Frangopol - Structural Safety, 2023 - Elsevier
Due to deep uncertainties associated with climate change and socioeconomic growth,
managing bridge networks faces the challenge to perform optimization for different …
managing bridge networks faces the challenge to perform optimization for different …
Physics descriptors enhanced Bayesian learning method for permeability of random media under sparse data
Permeability is a significant property in microstructure-based material design. Currently, the
main research gap in such material design can be divided into three aspects: Firstly …
main research gap in such material design can be divided into three aspects: Firstly …
Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators
A critical bottleneck for scientific progress is the costly nature of computer simulations for
complex systems. Surrogate models provide an appealing solution: such models are trained …
complex systems. Surrogate models provide an appealing solution: such models are trained …
Knowledge transfer for adaptive maintenance policy optimization in engineering fleets based on meta-reinforcement learning
Maintenance policy optimization is crucial for ensuring the efficient functioning of structures
and systems and mitigating the risk of deterioration. Reinforcement learning methods …
and systems and mitigating the risk of deterioration. Reinforcement learning methods …
Literature Review: Global Criticality Assessment Based on Feature Surrogates at the PCBA Levels
Reliability testing is essential in the PCBA (Printed Circuit Board Assembly) manufacturing
process since it helps to identify potential issues before they become significant in the future …
process since it helps to identify potential issues before they become significant in the future …
Knowledge representation-based hemispheric specialization of the brain
BP Bhuyan - Exploring Future Opportunities of Brain-Inspired …, 2023 - igi-global.com
Abstract Knowledge is an essential ingredient for the development of the majority of human
cognitive skills. The subject of how to define knowledge is a challenging one. Knowledge is …
cognitive skills. The subject of how to define knowledge is a challenging one. Knowledge is …