Optimizing HVAC energy efficiency in low-energy buildings: a comparative analysis of reinforcement learning control strategies under Tehran climate conditions
This study investigates the incorporation of advanced heating, ventilation, and air conditioning (HVAC) systems with reinforcement learning (RL) control to enhance energy efficiency in low-energy buildings amid the extreme seasonal temperatures of Tehran. We conducted comprehensive simulation assess...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-01-01
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| Series: | Data-Centric Engineering |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2632673625100142/type/journal_article |
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