Prediction of energy consumption in campus buildings using long short-term memory

In this paper, Long Short-Term Memory (LSTM) was proposed to predict the energy consumption of an institutional building. A novel energy usage prediction method was demonstrated for daily day-ahead energy consumption by using forecasted weather data. It used weather forecasting data from a local met...

Полное описание

Библиографические подробности

Главные авторы:	Muhammad Faiq, Kim Geok Tan, Chia Pao Liew, Ferdous Hossain, Chih-Ping Tso, Li Li Lim, Adam Yoon Khang Wong, Zulhilmi Mohd Shah
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Elsevier 2023-03-01
Серии:	Alexandria Engineering Journal
Предметы:	Energy consumption Long short-term memory Support vector regression Gaussian process regression Weather forecasting
Online-ссылка:	http://www.sciencedirect.com/science/article/pii/S1110016822008006
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!