期刊
SUSTAINABLE CITIES AND SOCIETY
卷 59, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.scs.2020.102190
关键词
Sensor deployment strategy; Indoor air quality (IAQ); Fuzzy cluster analysis; Artificial Neural Network (ANN); Low-dimensional Linear Ventilation Model (LLVM)
资金
- National Natural Science Foundation of China [51778385]
Sensor monitoring plays a very important role in indoor environment control and energy efficiency. However, it is always a challenging task when discussing the methods and strategy for sensor deployment, considering its numbers and locations. Thus, this work aims to provide a systematic methodology of sensor deployment for efficient indoor environment monitoring by using clustering method of Fuzzy C-means (FCM) algorithm. An experimental chamber was considered for ventilation basis. Low-dimensional Linear Ventilation Models (LLVM) were applied to generate a series of low-dimensional pollutant concentrations, representing the potential hypothetic monitoring data. FCM algorithm was then adopted to cluster these data as well as corresponding grid points classified by three zones, i.e., main flow, main diffusion and well-mixed zones. Then the cluster centers of each zone were determined representing as the locations of sensor deployment. Lastly, taking the cluster centers as the hypothetic sensor locations and corresponding concentrations as the input for LLVM-based ANN (Artificial Neural Network), the predicted volume-averaged CO2 concentrations agree well with the simulated ones directly from low-dimensional CFD results, with the maximal error of 6.5 %. This work will be further facilitating the realization of artificial intelligent ventilation system and efficient indoor environment control.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据