A Modified <i>γ</i>-Sutte Indicator for Air Quality Index Prediction

Abstract

Air pollution has become an essential issue in environmental protection. The Air Quality Index (AQI) is often used to determine the severity of air pollution. When the AQI reaches the red level, the proportion of asthma patients seeking medical treatment will increase by 30% more than usual. If the AQI can be predicted in advance, the benefits of early warning can be achieved. In recent years, a scholar has proposed an α-Sutte indicator which shows its excellence in time series prediction. However, the calculation of α-Sutte indicators uses a fixed weight. Thus, a β-Sutte indicator, using a dynamic weight with a high computation cost, has appeared. However, the computational complexity and sliding window required of the β-Sutte indicator are still high compared to the α-Sutte indicator. In this study, a modified γ-Sutte indicator, using a dynamic weight with a lower computational cost than the β-Sutte indicator, is proposed. In order to prove that the proposed γ-Sutte indicator has good generalization ability and is transferable, this study uses data from different regions and periods to predict the AQI. The results showed that the prediction accuracy of the γ-Sutte indicator proposed was better than other methods.

Keywords

• Air Quality Index
• <i>α</i>-Sutte indicator
• <i>γ</i>-Sutte indicator
• ensemble model
• prediction
• time series