Multi-fidelity Gaussian process regression fusing sparse experimental damage indices with simulated ones estimates damage state more accurately than single-fidelity GPs alone.
Towards Unified Probabilistic Rotorcraft Damage De- tection and Quantification via Non-parametric Time Series and Gaussian Process Regression Models,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models
Multi-fidelity Gaussian process regression fusing sparse experimental damage indices with simulated ones estimates damage state more accurately than single-fidelity GPs alone.