Academic Journal of Computing & Information Science, 2023, 6(10); doi: 10.25236/AJCIS.2023.061014.
Zhixuan Liu1, Jiayan Lin1, Lan Zhou1, Yupeng Song1, Xin Li2
1School of Computer and Communication Engineering, Nanjing Tech University Pujiang Institute, Nanjing, 211200, China
2School of Mechanical and Electrical Engineering, Nanjing Tech University Pujiang Institute, Nanjing, 211200, China
In recent years, air environment quality has become a hot issue of concern for people all over the world, and the prediction of air quality is of great significance for air pollution prevention and control. There is mainly a nonlinear relationship between air quality data and influencing factors, and BP neural network has a strong nonlinear mapping ability, which can fit the more complex nonlinear mapping relationship. Based on this, this paper utilizes BP neural networks to establish an air quality index AQI prediction model to predict the AQI in Nanjing, with an average relative error of about 1% and a prediction accuracy of 99%. The establishment of this model can provide reliable reference and decision-making basis for government departments and citizens.
BP Neural Networks, Air Quality, AQI Prediction
Zhixuan Liu, Jiayan Lin, Lan Zhou, Yupeng Song, Xin Li. Applied Research on AQI Prediction Based on BP Neural Network Modeling. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 10: 93-99. https://doi.org/10.25236/AJCIS.2023.061014.
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