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A unified utility function-based framework for prior-informed surrogate modeling
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DOI：10.1016/j.jprocont.2026.103785.png)
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Abstract
En 中文
• Unified UPriMo framework using utilities to blend data and priors. • Automatic, scale-free trade-off between heterogeneous prior losses. • Supports many priors: PDEs, monotonicity, stability, reference models.
Keywords:
Utility-function framework
Hybrid modeling
Physics-informed learning
Surrogate models
Thermal energy systems
Data-efficient AI
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