International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Air Pollution Prediction Model Using Artificial Neural Network And Fuzzy Theory

  • Baatarchuluun, Khaltar (Center for Advanced Image and Information Technology, School of Electronics & Information Engineering, Chon Buk National University) ;
  • Sung, Young-Suk (Center for Advanced Image and Information Technology, School of Electronics & Information Engineering, Chon Buk National University) ;
  • Lee, Malrey (Center for Advanced Image and Information Technology, School of Electronics & Information Engineering, Chon Buk National University)
  • Received : 2020.06.20
  • Accepted : 2020.07.02
  • Published : 2020.08.31
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Abstract

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper's aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.

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References

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