Published November 30, 2021 | Version v1
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PM2.5Concentration Prediction By Data Mining Method

  • 1. Department of Bachelor of Science, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam.
  • 2. Department of Computer Science, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam
  • 1. Publisher


The global air pollution is constantly increasing and causing negative effects on human health such as respiratory, cardiovascular diseases and cancers. Recently, pollution in Hanoi has become increasingly worse, especially when PM2.5 concentration is always at high level. Thus, PM2.5 prediction is of more urgency to issue early forecasts. Depending on air data including meteorological indicators and air pollution indicators collected in Hanoi, we have proposed a new characteristic extraction method that gave better results when uing the same algorithm compared to those of old methods. XGBoost algorithm was applied to predict the concentration of PM2.5 and the test showed that the accuracy of this algorithm is higher than that of other data mining algorithms while the training time is significantly lower.



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Journal article: 2278-3075 (ISSN)


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