Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach

• Main Authors: Mohd Herwan, Sulaiman, Zuriani, Mustaffa
• Format: Article
• Language: English; English
• Published: Elsevier Ltd 2024
• Subjects: QA75 Electronic computers. Computer science; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/41375/1/Chiller%20energy%20prediction%20in%20commercial%20building_A%20metaheuristic.pdf; http://umpir.ump.edu.my/id/eprint/41375/2/Chiller%20energy%20prediction%20in%20commercial%20building_A%20metaheuristic-Enhanced%20deep%20learning%20approach_ABS.pdf; http://umpir.ump.edu.my/id/eprint/41375/; https://doi.org/10.1016/j.energy.2024.131159; https://doi.org/10.1016/j.energy.2024.131159

Chiller energy prediction in commercial building : A metaheuristic-Enhanced deep learning approach Chiller systems hold a critical role in upholding comfort and energy efficiency within commercial buildings. Precise prediction of chiller energy consumption is imperative for operational optimization...