Air Quality Comprehensive Analysis System Based on Deep Learning
The Air Quality Index(AQI)is an important indicator for measuring the quality of environmental air.The ability to easily obtain air quality monitoring and forecasting data is of significant research value.Historical air quality data from Suzhou City from 2014 to 2020 were collected using web crawling technology.Based on Information Gain(IG)and Long Short-Term Memory networks(LSTM),the information gain of each pollutant on the AQI was calculated,and air quality forecasting was conducted.The experimental results show that,compared to the LSTM model,the proposed LSTM model based on information gain can predict the AQI more accurately.In addition,an air quality comprehensive analysis system has been established,which is rich in functions and intuitive,providing a scientific basis for the government and the public.
万方数据
维普
