Neural Parameter Estimation of RC Thermal Building Models for Model Predictive Control

arXiv:2604.05904 · eess.SY, cs.LG, cs.SY · Submitted 2026-04-07 · Read on arXiv

eess.SY, cs.LG, cs.SY

Submitted: 2026-04-07

Updated: 2026-09-25

Code: https://github.com/ThGaskin/NeuralABM

Terminology

• Transfer Learning — 12× in this paper · explained in 10 episodes
• Fine-Tuning — 9× in this paper · explained in 5 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Generalization — 5× in this paper · explained in 13 episodes
• Adam — 4× in this paper · explained in 2 episodes
• Inverse Problem — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Meta-learning — 2× in this paper · explained in 2 episodes
• System Identification — 2× in this paper · explained in 3 episodes
• Concept Drift — 1× in this paper · explained in 4 episodes
• Core — 1× in this paper · explained in 2 episodes
• Genetic Algorithms — 1× in this paper
• Interpretability — 1× in this paper · explained in 15 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Sim-to-Real Gap — 1× in this paper · explained in 6 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Hybrid modeling approach for better identification of building thermal network model and improved prediction
• Adam: A Method for Stochastic Optimization
• A Highly Configurable Framework for Large-Scale Thermal Building Data Generation to drive Machine Learning Research
• Deep transfer learning for system identification using long short-term memory neural networks

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