Air Pollutant Analysis and AQI Prediction Based on GRA and Improved SOA-SVR by Considering COVID-19

Ting Xu,Yanping Bai,Huichao Yan

doi:10.3390/atmos12030336

Abstract

Since COVID-19 pneumonia broke out, the Chinese government has taken a series of measures to control the spread of the epidemic, which has made the air quality of Taiyuan in February 2020 significantly better than during the same period in previous years. In this paper, the Gray Relational Analysis (GRA) method was first applied to evaluate and analyze the influence of six major pollutants on air quality. Then, the improved seagull optimization algorithm (ISOA) was proposed and combined with Support Vector Regression (SVR) to establish a hybrid predicted model ISOA-SVR. Finally, the proposed ISOA-SVR was utilized to predict air quality index (AQI). The experimental results on two kinds of different data showed that the proposed ISOA-SVR had the better generalization ability and robustness compared with other predicted models. Further, the proposed ISOA-SVR is suitable for the prediction of AQI.

Highlights

With the concentration of urban population and industrial growth, environmental pollution problems are arising
A prediction model of air quality index (AQI) in Taiyuan was established by using improved seagull optimization algorithm (ISOA)-Support Vector Regression (SVR) and compared with other predicted models
From the mean square error (MSE), relative mean square error (RMSE) and mean percentage error (MAPE) of the training results in Table 10, we found that the training results of ISOA-SVR (13.37973604, 0.163687428 and 28.1740733) were slightly worse than the best seagull optimization algorithm (SOA)-SVR (12.90917741, 0.162034198 and 28.71513087), but better than other algorithms

Summary

Introduction

With the concentration of urban population and industrial growth, environmental pollution problems are arising. Previous research showed that air pollution has a direct impact on human health. It is estimated that 1.22 million people are killed every year by haze in China, accounting for about 15% of annual deaths [1]. According to the data of the World Health Organization in 2018, air pollution causes seven million people to die of cancer, stroke, heart disease and respiratory diseases every year. Air pollution has become the number one killer of human beings. In 2019, the World Health Organization lists air pollution as one of the top ten threats to global health [2]

Methods

Results

Conclusion