T. He

Multi-Fidelity Gaussian Process Regression and Sequential Active Sampling for Surrogate Modeling: A Methodological Study with Validation on a Synthetic Radar Angle Tracking Benchmark

To address the challenge of limited evaluations of expensive high-complexity functions in surrogate modeling, this paper proposes a methodological framework that integrates multi-fidelity Gaussian process (MFGP) regression, sequential active sampling, and global sensitivity analysis, using a radar angle tracking accura...