Modeling occupant behavior in buildings
In the last four decades several methods have been used to model occupants' presence and
actions (OPA) in buildings according to different purposes, available computational power …
actions (OPA) in buildings according to different purposes, available computational power …
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Artificial neural network (ANN) has acquired noticeable interest from the research
community to handle complex problems in Construction and Building engineering (CB). This …
community to handle complex problems in Construction and Building engineering (CB). This …
Study on influencing factors for occupant window-opening behavior: Case study of an office building in **'an during the transition season
Y Gu, T Cui, K Liu, F Yang, S Wang, H Song, Q Qi… - Building and …, 2021 - Elsevier
Window-opening behavior profoundly affects indoor air quality, thermal comfort, and the
energy consumption of HVAC systems in office buildings. This paper presents the results of …
energy consumption of HVAC systems in office buildings. This paper presents the results of …
Deep learning models for building window-openings detection in heating season
The increasing use of monitoring systems such as Building Management System (BMS) or
connected devices bring the opportunity to better evaluate, model or control both occupants' …
connected devices bring the opportunity to better evaluate, model or control both occupants' …
Indoor environment data time-series reconstruction using autoencoder neural networks
As the number of installed meters in buildings increases, there is a growing number of data
time-series that could be used to develop data-driven models to support and optimize …
time-series that could be used to develop data-driven models to support and optimize …
[HTML][HTML] Deep learning for predictive window operation modeling in open-plan offices
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 …
operation modeling in open-plan offices. To achieve this, the study proposes a deep …
Day-ahead prediction of plug-in loads using a long short-term memory neural network
The aim of this work is to develop and validate a miscellaneous electric loads (MEL)
predictive model that does not require occupant-wise or building-wise model training nor …
predictive model that does not require occupant-wise or building-wise model training nor …