Urban air quality forecasting based on multi-dimensional collaborative Support Vector Regression (SVR): A case study of Beijing-Tianjin-Shijiazhuang.

Bing-Chun Liu,Arihant Binaykia,Cheng-Chin Tsao,Pei-Chann Chang,Manoj Kumar Tiwari,Chon-Lin Lee

doi:10.1371/journal.pone.0179763

Abstract

Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction.

Highlights

Air quality has a huge impact on the quality of living, the well-being of the population as well as the image of the city
The aim of this study is to present a new model for Air Quality Index (AQI) forecasting using collaborative multiple city air quality data as input
By conducting the three cities AQI forecasting experiments we have reached to the following conclusions: The RMSE values of the training and the testing datasets are

Summary

Introduction

Air quality has a huge impact on the quality of living, the well-being of the population as well as the image of the city. With the increase in population in urban areas, there has been an increase in the development of the industries as well as the consumption of fossil fuels. This has led to the increase in air pollution in China [1]. The dreadful effects of air quality in the capital city of China—Beijing due to increase in population which has led to increase in number of vehicles as well as increase in fuel consumption has been the point of discussion for many researchers [2].

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Results

Discussion

Conclusion