Design And Implementation Of Air Quality Point Location Optimization System Based On BiLSTM Improved Clustering

With the acceleration of the urbanization process,the air pollution problem,as an important part of the environmental protection work in China,has increasingly attracted public attention.People’s health is closely related to the distribution of air quality.If the real-time grasp of the distribution of air quality can be realized,it is very important for the choice of outdoor activities and the environmental governance work of environmental protection departments.Therefore,the establishment of a sound air quality monitoring network as soon as possible has become the key to quickly find and deal with air pollution problems.Air quality monitoring micro-station monitoring has become the key implementation plan of air quality monitoring network with its advantages of small size,mobile size,and no need for air quality monitoring network.However,with the continuous change of time and space,the problem of redundancy and reduced representation of sites has gradually emerged.And the air quality monitoring neutrino stations have a weak ability to resist sudden environmental factors,which easily leads to the lack of monitoring data.In view of the above problems,based on the application of Bi LSTM neural network for data supplement and combining with the clustering method for point point optimization,and design and realize an air quality monitoring point optimization system.This paper on the theory of neural network model and traditional air quality monitoring optimization method at the same time,to improve the accuracy of the monitoring data as the basic criterion,on the basis of traditional clustering,put forward a based on Bi LSTM neural network improve clustering point optimization method,in the air quality monitoring data is missing,apply Bi LSTM neural network supplement missing data.Compared with the traditional clustering method to optimize the air quality monitoring points,it can improve the accuracy of the monitoring point prediction,and provide effective help and support for the staff’s research and analysis.Finally,in order to better and more intuitive reflect the air quality monitoring results and better improve the work efficiency of air quality monitoring personnel,in Shenyang is located in hunnan 18 air quality monitoring micro station monitoring data as data support,implements a including user login,homepage,air quality and point information,monitoring point setting and optimization,data high value warning and other modules of air quality monitoring optimization system.Finally,through functional and non-functional tests,the system can meet the proposed application requirements,and provide certain technical support for accurately monitoring air quality and monitoring point optimization.