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Gaussian process fusion method for multi-fidelity data with . . . Highlights • We propose a novel Gaussian process fusion method for multi-fidelity data integration • Our method improves global modeling accuracy by 45% compared to traditional approaches • The adaptive weighting mechanism adjusts fusion weights dynamically based on sample density • The proposed method has been applied in the engineering design of aerospace vehicles