Research on Air Quality Forecasting Based on Big Data and Neural Network

Aiming at the problem that existing air quality prediction models cannot efficiently and accurately predict air quality in a big data environment, an air quality prediction method based on a big data platform to implement a distributed neural network is proposed. Collect historical data of the six pollutant concentrations that affect the air quality index and use it as input to a neural network model; A distributed neural network model containing the AQI change rule in the distributed neural network structure is adopted to realize the short-term prediction of the AQI. Experimental results show that air quality prediction models based on big data and neural networks can reveal the development trend of air quality through self-learning characteristics. And has higher prediction accuracy, It can provide a scientific basis for the degree of urban air pollution and help people make appropriate measures for different AQI levels.