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...
محفوظ في:
| المؤلفون الرئيسيون: | , , |
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| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Elsevier LTD
2025
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| الموضوعات: | |
| الوصول للمادة أونلاين: | 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 |
| الوسوم: |
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الانترنت
http://umpir.ump.edu.my/id/eprint/44263/1/Feature%20Optimization%20with%20Metaheuristics%20for%20Artificial%20Neural%20Network-based%20Chiller%20Power%20Prediction.pdfhttp://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