Research On Water Environment Real-time Monitoring Of The Three Gorges Reservoir Area And Water Quality Evaluation Algorithm

The Three Gorges Reservoir Area is the national important strategic freshwater reserve.Since secondary reservoir impoundment,the water environment problems raised obviously due to the decrease of flow rate in relevant basin and self-purification capacity.Therefore,the monitoring and water quality assessment of the water environment in the Three Gorges reservoir area has become a hot issue in this field.The factor sample data of reservoir water is multi-factors,high dimension and big data characteristics.The traditional off-line water quality monitoring and water quality evaluation method is difficult to accurately characterize the actual situation of reservoir water quality.In order to overcome the shortcomings of the existing technology,this paper proposes to build a real-time online and off-line of water quality monitoring methods.On this basis,a water quality evaluation algorithm for water environment monitoring in the Three Gorges reservoir area is established.The research work of this paper has important theoretical value and practical significance for improving the water environment monitoring and water quality assessment theory of the Three Gorges reservoir area.The major contributions of the paper are summarized as follows:(1)Wireless Sensor Networks(WSN)is low cost,high fault tolerance and has a wide distribution,as well as real-time monitoring function.Combined with special applications of the Three Gorges Reservoir Area,we approach a fusion of wireless sensor network,GPRS and Internet.Then we build a massive real-time monitoring system applies to water quality of Three Gorges Reservoir Area,achieving intelligence and networking of the climate monitoring,and use the system to collect a large number of real-time monitoring of water quality parameter data.Through the statistical analysis of these data,we can get the water environment of the reservoir area.(2)In order to accurately assess the water quality of the reservoir area,a large number of water quality parameters collected in real time need to be clustered.For the phenomenon of single point deletion in the sample point of the monitored water quality factor sample data,the missing value is filled by the nearest mean interpolation method.For the characteristics of multi-factor and high dimension of sample data,the data is dimensioned by principal component analysis(PCA).Finally we get 1200 sets of experimental sample data.(3)On the basis of studying the existing mainstream clustering analysis algorithm,we find that the traditional K-means clustering algorithm has a strong dependence on the initial clustering center.In this paper,an improved K-means clustering algorithm is proposed for the introducing proportion of neighboring areas(PNA).The algorithm can determine the initial clustering center and accelerate the convergence.According to the temporal and fuzzy characteristics of water quality data in the Three Gorges Reservoir Area,a fuzzy C-means(FCM)clustering algorithm is introduced.FCM clustering algorithm solves the clustering results existing either-or problem of hard clustering algorithm.(4)For the problems of FCM clustering algorithm,for example,the initial clustering center is sensitive,easy to fall into the local optimal and so on,a K-FCM clustering algorithm is proposed.The algorithm uses the improved K-means clustering algorithm to guide the initial clustering center of FCM clustering algorithm,which accelerates the algorithm convergence.Finally,three clustering algorithms are analyzed and compared by experiment simulation and sample data is analyzed by K-FCM clustering algorithm.A new water quality evaluation standard is constructed,and the water quality of the reservoir area in the past three years is evaluated scientifically.(5)We summarize the work and point out and forecast the next work of this paper.