Enhancing Day-Ahead Cooling Load Prediction in Tropical Commercial Buildings Using Advanced Deep Learning Models: A Case Study in Singapore
Commercial buildings in hot and humid tropical climates rely significantly on cooling systems to maintain optimal occupant comfort. A well-accurate day-ahead load profile prediction plays a pivotal role in planning the energy requirements of cooling systems. Despite the pressing need for effective d...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-02-01
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Series: | Buildings |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-5309/14/2/397 |