The Application Of Principal Component Analysis And Artificial Neural Network On Water Quality Evaluation In Poyang Lake

Poyang Lake is the main lake in Jiangxi province, and also is the largest freshwater lake in our country, It has abundant rich water resources and biological resources. With a flood storage, shipping, irrigation, aquaculture and tourism and many other features. The environmental protection of Poyang Lake water has always been a well-focused topic.In this paper, it is start from that the Poyang Lake water quality characteristics of environmental monitoring data. Study how to use the information fusion technology in the Poyang Lake's water quality monitoring data processing, reduces the uncertainty of the water quality information processing, get more precise evaluation of the results of water quality. This is to obtain objective and accurate water quality in water bodies, analysis of water quality trends, provide a scientific basis for decision-making of the Poyang Lake's water environment protection.In the large quantities of information processing of the water quality of Poyang Lake, first, application of principal component analysis processing with SPSS software , we can see that Poyang Lake was found contaminated mainly by eutrophication, This indicates that Poyang Lake has the trend of eutrophication. And then right to assess the nutritional status of Poyang Lake with the BP neural network, The results show that Poyang Lake is in the development stage of nutrition to nutrient-rich, it should be noteworthy. The results also confirmed that this is a more effective evaluation methods, principal component analysis method combined with neural network in the multi-source water treatment. The greatest feature of it is that it combines the advantages of both. Not only avoiding the traditional arbitrary subjective quality evaluation methods, but aslo can automatically filter the sample and objective evaluation for the samples of each indicator.