An integrated approach of Belief Rule Base and Convolutional Neural Network to monitor air quality in Shanghai
作者：
Highlights：
• We monitor air quality from satellite images to address spatial coverage limitation.
• We customize Convolutional Neural Network (CNN) to analyze satellite images.
• We propose mathematical model to integrate CNN with Belief Rule Based Expert System.
• We check Relative Humidity to distinguish hazy image between cloud and polluted air.
• We address uncertainties of environmental sensor data by this expert system.
摘要
•We monitor air quality from satellite images to address spatial coverage limitation.•We customize Convolutional Neural Network (CNN) to analyze satellite images.•We propose mathematical model to integrate CNN with Belief Rule Based Expert System.•We check Relative Humidity to distinguish hazy image between cloud and polluted air.•We address uncertainties of environmental sensor data by this expert system.
论文关键词：Air quality monitoring,Belief Rule Based Expert System (BRBES),Convolutional Neural Network (CNN),Uncertainty
论文评审过程：Received 23 January 2022, Revised 15 June 2022, Accepted 15 June 2022, Available online 20 June 2022, Version of Record 23 June 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.117905
