Design And Implementation Of Water Quality Point Optimization System Based On Neural Network Dimensionality Reduction And Clustering

Water,a necessary substance for mankind to survive on the earth.With the rapid development of the times and the improvement of living standards,the impact of industrialization on the water environment is increasing around the world.In the past,we can always hear some news about water pollution in a certain area.For example,the industrial waste water discharged from the factory polluted a river.Another example,domestic sewage in certain areas has caused pollution of downstream waters.With people’s governance,these environmental problems have gradually improved.People regard the protection and rational use of environmental resources as an important task to complete the sustainable development of the environment and economy.Relevant departments are paying more and more attention to the management and monitoring of water resources.Accurate water resources monitoring and reasonable water quality point management can provide data support for water quality governance.Therefore,the optimization of water quality points has practical application significance.Simultaneously,the advancement of science and technology and the improvement of computer performance provide technical support for the optimization of water quality points.Based on the water quality point monitoring data and artificial neural network,this paper realizes a water quality point optimization system.In order to improve the accuracy of monitoring water quality data,this paper studies the traditional water quality point optimization method.On this basis,the artificial neural network is used to optimize it.Based on the results of various water quality points and the water quality data of each point,I designed and implemented a water quality point optimization system based on neural network dimensionality reduction clustering.This system uses auto encoder neural network to optimize the traditional water quality point monitoring method.With water quality and section data as data support,I designed and completed seven modules,which include user login module,monitoring information module,water environment operation and maintenance monitoring module,over-standard prompt module,monitoring point setting and optimization module,system notification module and management module.Finally,after functional testing and non-functional testing,the system achieved the expected effect and met the application requirements.