Research And Implementation Of Data Mining Algorithm For Environmental Information

In recent years,the economy of China has developed rapidly.But at the same time,the environment has been polluted to varying degrees.In order to reflect the changing trend of air pollution,strengthen air pollution prevention management and prevent serious air pollution incidents happening,it is significant to forecast air quality and air pollution emissions of pollution sources,which needs to judge the authenticity of the data.This thesis mainly focuses on the following work:Firstly,in the prediction of PM_2.5 concentration,the Markov chain is used to study the correlation between PM_2.5 concentration and the concentration of PM_2.5 in the first few hours,which can predict and analyze the PM_2.5 pollution grade.In order to predict the specific value of PM_2.5 concentration,the random forest is used to predict the specific value of PM_2.5 concentration.The analysis results show that using Markov chain to predict the PM_2.5 pollution level can get the higher accuracy.The random forest method in machine learning can predict the specific value of PM_2.5concentration,and the prediction results are good.Secondly,in order to prevent the occurrence of air pollution,the thesis analyzes the pollution emission of polluting enterprises.In this thesis,the wavelet neural network is used to predict the concentration of sulfur dioxide and nitrogen oxide emissions from polluting enterprises.In this thesis,the local outlier analysis algorithm based on density is used to judge the pollution concentration value of the pollution source,and to judge whether the pollution data provided by the enterprise is suspicious.Thirdly,in order to understand the influence of polluted gas on air quality,this thesis uses the AERMOD model to analysis the spread of pollutants,then Kriging interpolation is employed to render atmospheric dispersion modeling results.Finally,this thesis displays the space distribution of pollutant emissions using ArcGIS.By this way,we can know the effect of polluted gas on air quality.Fourthly,the software design and implementation of the model are discussed.Using WinForm technology,the system software is based on the.NET platform.The development process is based on object-oriented thinking,and the programming language of the system software is C#.The system can visually display the prediction results of PM_2.5,the prediction results of the pollutant emission concentration,the results of the pollutant discharge concentration data and the spatial distribution of the pollutants.