Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction
Building energy efficiency is crucial for global sustainability efforts, with chillers representing major energy consumers in commercial buildings. Accurate prediction of chiller power consumption remains challenging due to complex operational parameters, with feature selection being critical for mo...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier LTD
2025
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/44263/1/Feature%20Optimization%20with%20Metaheuristics%20for%20Artificial%20Neural%20Network-based%20Chiller%20Power%20Prediction.pdf http://umpir.ump.edu.my/id/eprint/44263/ https://doi.org/10.1016/j.jobe.2025.112561 https://doi.org/10.1016/j.jobe.2025.112561 |
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