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Air Quality Prediction Model Based on Grey Interval

The air pollutants concentration is affected by various recent factors such as the weather, environmental conditions and the season. For this reason, this study used grey interval GM(1,1) prediction model whose research object is small data to predict the air quality grade and major pollutants. The experimental results show that the model for air quality grade of prediction accuracy is 75%, and the primary pollutant can be well found by the prediction results of the major pollutants. In addition, it is found that the prediction values of pollutant concentration are impacted by the degree of data fluctuation, which also indirectly affects the accuracy in predicting air quality grade and the primary pollutant.