Analysis Of Hydraulic Elements In The Middle Route Of South-to-North Water Transfer Project Based On Data Mining Technology

As a long-distance water transfer project,the South-to-North Water Diversion Project is the largest water transfer project in the world today.It is beneficial to alleviating the problem of water shortage in northern China and is of great significance to promoting economic development and improving the ecological environment in the north.The middle route of the South-to-North Water Diversion Project has a long water transfer distance,many buildings along the route,and many hydraulic elements.Therefore,studying the main hydraulic problems of the middle route is the key to ensuring operation scheduling and safe and stable water delivery.In this paper,starting from the hydraulic problems of the South-to-North Water Transfer Project,based on the hydraulic model of the open channel water delivery system and the measured water regime data in the center,a PSO-BP neural network model based on the information diffusion method and a particle swarm algorithm calibrating hydraulic parameter model are established.,And respectively used in the analysis and calculation of gate outflow,water surface line and channel roughness.The main research results are as follows:(1)The particle swarm optimization algorithm is applied to the calibration of hydraulic parameters of the outflow from the gate hole.Based on the measured water regime data and basic parameters of the control gate in the middle route of the South-to-North Water Transfer Project,the flow pattern of the gate orifice was judged,and the particle swarm algorithm model was established to calibrate its discharge coefficient and submergence coefficient.(2)Apply the particle swarm optimization algorithm to the channel roughness determination.10 canal sections in the middle line are selected,and the comprehensive roughness value of the canal sections is optimized and calculated according to the measured data of each canal section.The results show that the method has certain applicability in the calibration of hydraulic parameters.(3)Establish a PSO-BP neural network model based on the information diffusion method,and use it in the analysis of outflow from the control gate hole of the mid-line of the South-to-North Water Transfer Project and the analysis and calculation of the channel water surface line.The results show that the established neural network model has high fitting accuracy,and the fitting accuracy of the data processed by the information diffusion method can be further improved.In short,this research is based on the South-to-North Water Transfer Project as the background,combined with information diffusion theory,particle swarm optimization algorithm and BP neural network model to solve hydraulic problems,and enriches the solutions to hydraulic problems in the center.The application of data mining technology also provides method reference for reducing relative error and improving accuracy when solving related hydraulic problems.For other similar water transfer projects,solving the problems of related hydraulic elements has promotion and application value.