Universiti Teknologi MARA, Malaysia
The daily monitoring, accurate data analysis, quality prediction and visualization of air quality (AQ) are conducive to the overall control of urban AQ. This paper mainly carries on the research about the artificial neural network in the field of environment. This paper aims at exploring intelligent prediction methods, improving intelligent prediction algorithms and establishing intelligent prediction models for AQ. The combination of time series ARMA model and BP neural network(BPNN) can give full play to their advantages. In this paper, the combined model of ARMA. BPNN is established to predict AQ Index (AQI). The experimental results show that the state information displayed by the simulation is basically consistent with the actual AQ, and the accuracy is more than 85%. This shows the practicability of the model proposed in this paper, which can be used in actual AQ prediction and is conducive to the development of environmental monitoring work.
Neural Network, Air Quality, Combined Model, Prediction Model
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