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Titel:

Deep learning for predictive window operation modeling in open-plan offices

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Banihashemi, F.; Weber, M.; Lang, W.
Abstract:
This study explores how the past, both short and long-term, affects the predictive window operation modeling in open-plan offices. To achieve this, the study proposes a deep learning method that uses long short-term memory (LSTM) artificial neural networks. The proposed model is an ensemble of LSTM networks that utilize relevant indoor environmental data from multiple sensory systems and weather data from a nearby weather station to predict the window state with different predictive horizons. Th...     »
Stichworte:
NuData_Campus
Zeitschriftentitel:
Energy and Buildings
Jahr:
2024
Band / Volume:
310
Seitenangaben Beitrag:
114109
Volltext / DOI:
doi:10.1016/j.enbuild.2024.114109
Verlag / Institution:
Elsevier BV
E-ISSN:
0378-7788
Publikationsdatum:
01.05.2024
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