Research And Implementation Of Water Resource Data Cleaning And Reorganization Algorithm

Since ancient times,China has been continuously researching hydrology,and the hydrology industry has a profound impact on the people’s livelihood in China.Therefore,the rational development and utilization of water resources and the optimization of the allocation of water resources can achieve the effect of promoting the sustainable development of the national economy.Nowadays,there is a need to process hydrological and water resources data in China,based on which a water resources data cleaning and compilation system is planned to be developed.The authors analyze and summarize the current research status of water resources data cleaning and compilation,and introduce and compare the existing data fitting algorithms and interpolation algorithms,and finally innovatively optimize and summarize the efficient data cleaning and compilation scheme as the algorithm of water resources data cleaning and compilation system,and lay the corresponding foundation for the design and development of water resources data cleaning and compilation platform.This paper firstly demonstrates the possibility of developing the water resources data cleaning and compilation system under the current technical conditions,then designs the system based on the current required functions,then selects the corresponding technology and software according to the system requirements and carries out the design and implementation of the water resources data cleaning and compilation system.JS as the development framework,IDEA and Data Grip as the development tools,and finally the system was tested using relevant test cases.This paper finally developed a relatively complete function and good performance of the water resources data cleaning and rectification system,the main innovations of the system are.1、Innovative use of segmental interpolation,through the short time,medium time,long time interpolation three ways to different time span of hydrological water resources data for targeted interpolation.2 、 By analyzing the distribution characteristics of water level and flow data detected by different hydrological stations,we determine the corresponding threshold values of water level data corresponding to different times and locations for preliminary determination,and then judge the abnormal values through the Lajda criterion and box plot method.3、Through the process of curve fitting to find the water level flow relationship,we will clean the data after interpolation and the corresponding curve to fit the judgment,and finally the corresponding water level flow relationship curve,so as to achieve the effect of a key rectification.At this stage we choose three different types of fitting functions,polynomial,logarithmic and exponential,to fit the curve,and on top of this,introduce a least squares fitting coefficient R squared,and finally choose the one with the largest value of the least squares fitting coefficient as the best fit;if the fitting coefficient of least squares is less than 0.9,it means that the data fit for this year is abnormal.