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Analysis and Modeling of Mechanical Ventilation Operation Behaviors of Occupants in Cold Regions of North China

Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
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Author to whom correspondence should be addressed.
Academic Editor: José A.F.O. Correia
Appl. Sci. 2022, 12(10), 5143; https://doi.org/10.3390/app12105143
Received: 25 April 2022 / Revised: 14 May 2022 / Accepted: 17 May 2022 / Published: 19 May 2022
(This article belongs to the Section Environmental Sciences)
Mechanical ventilation has a great impact on building simulation performance, such as indoor environment quality and building energy consumption. However, there is still a lack of accurate mechanical ventilation models established from long-term field data that can effectively predict building performance. In this study, one-year measurements on mechanical ventilation operation behavior were collected from 85 apartments, which were conducted with a mechanical ventilation system of the same brand in cold regions of North China. This permitted statistical analysis and clustering of the mechanical ventilation operation behavior by using the K-means method, leading to five behavior patterns. The results showed that 24% households operated mechanical ventilation system nearly all day, and there was a large difference in usage behaviors between the split system and the centralized system. Furthermore, two classes of models based on random forest and logistic regression were developed for predicting mechanical ventilation system operation (on/off) behavior. The models based on random forest showed high accuracy as it resulted in a 0.992 average in predictions. These models using field data can guide the selection of accurate input boundary conditions of mechanical ventilation and improve the accuracy of dwelling numerical simulations. View Full-Text
Keywords: mechanical ventilation operation behavior; machine learning; predictive model; residential building mechanical ventilation operation behavior; machine learning; predictive model; residential building
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MDPI and ACS Style

Zhang, C.; Sun, H. Analysis and Modeling of Mechanical Ventilation Operation Behaviors of Occupants in Cold Regions of North China. Appl. Sci. 2022, 12, 5143. https://doi.org/10.3390/app12105143

AMA Style

Zhang C, Sun H. Analysis and Modeling of Mechanical Ventilation Operation Behaviors of Occupants in Cold Regions of North China. Applied Sciences. 2022; 12(10):5143. https://doi.org/10.3390/app12105143

Chicago/Turabian Style

Zhang, Chenchen, and Hejiang Sun. 2022. "Analysis and Modeling of Mechanical Ventilation Operation Behaviors of Occupants in Cold Regions of North China" Applied Sciences 12, no. 10: 5143. https://doi.org/10.3390/app12105143

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