Design And Implementation Of Air Pollution Simulation And Prediction System Based On GIS

In recent years,with the progress of our society and economic development,the process of urbanization and industrialization has been accelerating.However,with the rapid economic development comes the environmental pollution problems caused by the extensive development model of high energy consumption and low output in China,especially the frequent occurrence of air pollution incidents in recent years.Air pollution not only endangers people's health and brings inconvenience to people's daily lives,but also restricts human survival and social development.Therefore,it is necessary to understand the diffusion and migration of air pollution,the analysis of air pollution and the prediction of air pollution by effective methods are necessary for the environmental departments and institutions to carry out air pollution supervision and control and auxiliary decision-making.The air pollution diffusion model is a complex mathematical model that simulates the diffusion of air pollutants based on the law of pollutant diffusion and migration,and the equivalent of the pollution source and the weather data at that time.The results obtained by using the air pollution diffusion model are usually data texts,and the visual presentation cannot be combined with spatial information for analysis and decision making.GIS has powerful spatial data visualization and spatial analysis capabilities.Therefore,the effective combination of the two can better simulate,predict,analyze,and demonstrate the spread of air pollution.On the basis of the analysis of the domestic and foreign research status,the main factors affecting the atmospheric diffusion are deeply analyzed.The Gauss difusion model,BP neural network and other mathematical theories are deeply studied,and the method of determining the parameters of the diffusion model is analyzed.On this basis,the adaptive learning rate is used to improve the BP neural network.It improves the learning rate of BP neural network and speeds up the learning rate of BP neural network.The method of air pollution analysis and GIS combination is discussed.The boundary and initial conditions of pollution diffusion are determined by GIS technology.Air pollution data processing and spatial analysis are carried out.Spatial interpolation method is used to visualize the results of pollution data processing.Finally,based on the ArcGIS Engine component technology,the air pollution diffusion and prediction system is developed based on the.NET and Visual Studio integrated development environment,and the functions of air pollution data processing,query statistics,air pollution diffusion simulation and air prediction pollution pretest based on BP neural network are realized.It effectively realizes the storage,management,analysis and visualization of air pollution data.This study integrates GIS and air pollution diffusion and prediction models,which can effectively simulate and predict air pollution,and provide technical support and decision-making for air pollution control and research for MEP departments and agencies.