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A platform for research: civil engineering, architecture and urbanism
Determinants of manual window control for natural ventilation in homes
https://orcid.org/0000-0003-1877-3493
https://orcid.org/0000-0002-5391-3298
Abstract Understanding energy-related occupant behavior can improve the energy efficiency of homes. Natural ventilation is one of the energy-related complex occupant behavior which influences both the thermal environment and indoor pollutants levels. The objective of the present study is to find determinant parameters of occupant behavior related to the manual control of windows for natural ventilation in homes. The field monitoring was carried out in thirteen sample homes from December 7, 2017, to December 31, 2022. The importance of twenty outdoor and indoor physical parameters was calculated by the Random Forest algorithm from the data set of the sample homes. The importance of the parameters changed from sample home to sample home and from season to season. And there was also a clear difference between the driving parameters for opening and closing windows in the sample homes. The Random Forest algorithm predicted both window opening and closing behavior with high accuracy when the outdoor and indoor seven parameters were applied. The results of the present study could be applied to develop occupant behavior models that can be implemented in energy simulation tools.
Highlights The determinants of manual control of windows varies from home to home. The driving parameters for window opening are different from the closing windows. There is no typical set of determinants applying to all homes. More than seven parameters increase the average cumulative importance up to 60%.
Determinants of manual window control for natural ventilation in homes
https://orcid.org/0000-0003-1877-3493
https://orcid.org/0000-0002-5391-3298
Abstract Understanding energy-related occupant behavior can improve the energy efficiency of homes. Natural ventilation is one of the energy-related complex occupant behavior which influences both the thermal environment and indoor pollutants levels. The objective of the present study is to find determinant parameters of occupant behavior related to the manual control of windows for natural ventilation in homes. The field monitoring was carried out in thirteen sample homes from December 7, 2017, to December 31, 2022. The importance of twenty outdoor and indoor physical parameters was calculated by the Random Forest algorithm from the data set of the sample homes. The importance of the parameters changed from sample home to sample home and from season to season. And there was also a clear difference between the driving parameters for opening and closing windows in the sample homes. The Random Forest algorithm predicted both window opening and closing behavior with high accuracy when the outdoor and indoor seven parameters were applied. The results of the present study could be applied to develop occupant behavior models that can be implemented in energy simulation tools.
Highlights The determinants of manual control of windows varies from home to home. The driving parameters for window opening are different from the closing windows. There is no typical set of determinants applying to all homes. More than seven parameters increase the average cumulative importance up to 60%.
Determinants of manual window control for natural ventilation in homes
https://orcid.org/0000-0003-1877-3493
https://orcid.org/0000-0002-5391-3298
Abstract Understanding energy-related occupant behavior can improve the energy efficiency of homes. Natural ventilation is one of the energy-related complex occupant behavior which influences both the thermal environment and indoor pollutants levels. The objective of the present study is to find determinant parameters of occupant behavior related to the manual control of windows for natural ventilation in homes. The field monitoring was carried out in thirteen sample homes from December 7, 2017, to December 31, 2022. The importance of twenty outdoor and indoor physical parameters was calculated by the Random Forest algorithm from the data set of the sample homes. The importance of the parameters changed from sample home to sample home and from season to season. And there was also a clear difference between the driving parameters for opening and closing windows in the sample homes. The Random Forest algorithm predicted both window opening and closing behavior with high accuracy when the outdoor and indoor seven parameters were applied. The results of the present study could be applied to develop occupant behavior models that can be implemented in energy simulation tools.
Highlights The determinants of manual control of windows varies from home to home. The driving parameters for window opening are different from the closing windows. There is no typical set of determinants applying to all homes. More than seven parameters increase the average cumulative importance up to 60%.
Determinants of manual window control for natural ventilation in homes
Park, J.S. (author) / An, Young-Min (author) / Jeong, Jae-Weon (author)
Building and Environment ; 244
2023-08-14
Article (Journal)
Electronic Resource
English