Quantitative Analysis Of Chemical Pollution Such As Ammonia Nitrogen In The Chaohu Lake Basin

Currently,for the eutrophic chemical pollution such as ammonia nitrogen in the Chaohu Lake Basin,the following problems need to be solved: 1.The traditional calculation method often uses the formula calculation method to calculate the chemical pollution problem,which is not suitable for the current situation where the amount of data is too large;2.Pollution data collection The format is not standardized;3.Lack of a unified platform to store the collected data.However,with the improvement of computing power,the machine learning algorithm model often has natural processing advantages for problems with a large amount of data.Therefore,to solve the above-mentioned problems,three aspects of the machine learning algorithm model,standardization research,and collection and judgment system are used to analyze the chemistry of Chaohu Lake Basin.Quantitative analysis of pollution.The main work is as follows:(1)Using a machine learning algorithm model to model the chemical pollution data of Chaohu Lake Basin.According to the strong sensitivity of the chemical pollution data such as ammonia nitrogen in the Chaohu Lake Basin to external conditions and the non-linearity and instability of the pollution data,a random forest algorithm model based on high-correlation filtering was proposed,and the chemical pollution such as ammonia nitrogen in the Chaohu Lake Basin was constructed.Concentration prediction model.This method uses high-correlation filtering to eliminate the strong correlation between water pollution data and adjusts the parameters of the random forest model to make the training data achieve the best prediction effect.At the same time,real data sets are used for model testing.After the comparative experiments of Bayesian Ridge regression model,ordinary linear regression model,elastic network regression model,support vector machine model,and correlation vector machine model,the experimental results are in COD,NH3 N,TN,and TP The above MAE evaluation indicators are 1.95162,0.065709,0.146852,and 0.879808 respectively.The average error of 10 experiments is calculated,and the final error result is 0.14%.On the whole,it is verified that the proposed highcorrelation filtering random forest algorithm model has a good prediction effect.(2)Formulate standardized documents for the collection of pollution data in the Chaohu Lake Basin.In the study of eutrophication chemical pollution such as ammonia nitrogen in the Chaohu Lake Basin,to unify and standardize the data format collected by different departments,this project first divided the pollution sources into rural life pollution sources,planting pollution sources,livestock Poultry breeding industry pollution sources,and aqua,culture pollution sources are divided into four categories,and further divided into rural domestic sewage data,rural solid waste data,planting chemical fertilizer and pesticide data,planting mulch data,planting straw data,and livestock and poultry breeding industry pollution sources according to the collection content.Data and aquaculture pollution source data are collected in seven pieces.Secondly,jointly with Anhui Product Quality Supervision and Inspection Research Institute and Hefei Zhongke Guoyu Intelligent Engineering Co.,Ltd.to participate in the collection and evaluation of pollution data in the Chaohu Lake Basin.Finally,determine the work that needs to be done before,during,and after collecting data and the format requirements corresponding to the collected content.(3)Design and implementation of the chemical pollution collection and justice system in the Chaohu Lake Basin.In order to store the pollution data of the Chaohu Lake Basin collected by the front-line collectors,a chemical pollution collection and judgment system for the Chaohu Lake Basin was designed and implemented.Through this system,the front-line collectors can collect data anytime and anywhere and save it in the main database.At the same time,the system also combines The abovementioned high-correlation filtering random forest algorithm model to realize the function of analyzing and predicting the future chemical pollution situation.In summary,based on the research of the high correlation filter random forest algorithm model,standardized documents,and collection and judgment system,it has certain practical significance to research the quantitative analysis of chemical pollution in the Chaohu Lake Basin.