Hybrid GPR-DNN Enhanced NSGA-II
Published: 19 January 2026| Version 1 | DOI: 10.17632/277bcf335f.1
Contributor:
Yuefeng LiDescription
It constructs a deep learning optimization framework based on Gaussian Process Regression (GPR)-enhanced data augmentation. This approach leverages the Bayesian inference capabilities of GPR to interpolate between sparse samples, thereby enabling the neural network to capture complex physical features that conventional methods might miss.
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Thermal Analysis