Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer
This paper addresses the critical challenge of energy efficiency in commercial buildings, where chillers typically consume 40–50% of total building energy. Accurate forecasting of chiller power consumption is essential for optimizing building energy management systems and reducing operational costs....
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Next Energy |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949821X25000845 |
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