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Showing 1 to 1 of 1 for “"Generative Data Augmentation"”.
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ENHANCING BUILDING FAULT DETECTION, DIAGNOSTICS, AND PROGNOSTICS THROUGH A HYBRID PHYSICS-INFORMED MODELING FRAMEWORK FOR OVERCOMING QUANTITY AND TEMPORAL DATA SCARCITY
… hindered by the scarcity of real-world fault data. This thesis proposes a hybrid physics-informed modeling framework to overcome both data quantity scarcity and temporal sparsity. First, Hybrid Conditional Generative Adversarial Network (HCGAN) is developed. By leveraging physics-based …