Indoor Air Pollution Source Localization Based on Small-Sample Training Convolutional Neural Networks

Indoor Air Pollution Source Localization Based on Small-Sample Training Convolutional Neural Networks

In addressing the problem of indoor air pollution source localization, traditional methods have limitations such as strong sample dependence and low computational efficiency. This study uses a convolutional neural network to establish a pollution source inversion method based on small samples. By in...

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Bibliographic Details
Main Authors: Tiancheng Ye, Mengtao Han
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Buildings
Subjects:
pollution source inversion
convolutional neural network (CNN)
deep learning
small sample
spatial localization accuracy
Online Access:https://www.mdpi.com/2075-5309/15/8/1244
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