Deep Learning Framework Using Transformer Networks for Multi Building Energy Consumption Prediction in Smart Cities

Deep Learning Framework Using Transformer Networks for Multi Building Energy Consumption Prediction in Smart Cities

The increasing complexity of urban building energy systems necessitates advanced prediction methods for efficient energy management. Urban buildings account for approximately 40% of global energy consumption, making accurate prediction crucial for sustainability goals. This research develops a novel...

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Bibliographic Details
Main Authors: Samuel Moveh, Emmanuel Alejandro Merchán-Cruz, Maher Abuhussain, Yakubu Aminu Dodo, Saleh Alhumaid, Ali Hussain Alhamami
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Energies
Subjects:
building energy prediction
deep learning
smart cities
transformer networks
urban computing
Online Access:https://www.mdpi.com/1996-1073/18/6/1468
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