Heterogeneity Design In The Air Quality Monitoring System And PM10 Grey Prediction

With the improvement of degree of industrialization, and traffic convenient and human the improvement of the standard of living, air pollution also has more and more serious damage to human beings. The thesis takes hubei city air quality automatic monitoring control system topics as their background to do grey prediction research on the air quality based on GM(1,1) grey modeling .The thesis designs the air quality monitoring system, then research system heterogeneity from equipment, data and agreement, and puts forward a kind of automatic monitoring system heterogeneous solutions of abstract device, virtual agreement and mapping data, and efficiently solve the domestic and foreign various testing instrument and different transmission agreements problem which provides a foundation for prediction based on detecting data. This thesis expounds influence factors on the air quality, such as sulfur dioxide, nitrogen oxides, carbon monoxide, ozone and PM10, and makes PM10 the main pollution factor. Research grey prediction model relevant theories about the grey system theory , then chose grey forecast modeling methods in air quality prediction, and design the GM (1, 1) grey forecasting model, and forecast the air quality. The model for prediction of sudden factors exists deficiencies, then this thesis proposes improvement scheme, and fully considers sudden factors, and uses an estimated experience value and average level concepts processed the original sequence , and reduces the sudden factors error, and raises the accuracy.The thesis studies indicated that the air quality modeling based on gray prediction research is feasible, and acquire higher precision and reliability, for countermining air quality prediction practice provided a feasible method.