Application of data mining technology and intelligent information technology in the construction and management of the water conservancy project in Area A

Abstract

A water conservancy project for the construction of foundation engineering is indispensable. Its development is very important to ensure the quality of the construction level and management and to ensure that the construction of water conservancy projects works in the direction of automation. The present water conservancy project construction and management is inefficient, hydrology prediction errors are prevalent, and the utilization rate of water resources is low. To address these issues, this paper will apply data mining technology and intelligent information technology in water conservancy project management. This helps to study better the construction and management of water conservancy projects. By employing data mining techniques, valuable data from water conservancy projects will be extracted and analyzed. The first step involves gathering the relevant data from the projects and subjecting it to data mining processes. Through careful analysis and evaluation of the data, we can predict the runoff in the reservoir hydrology of Area A. Experimental results demonstrate that utilizing data mining techniques to predict the runoff of Reservoir A from January to December 2020 yielded a difference of 3.44% between the maximum and minimum values. Furthermore, employing machine learning techniques for prediction resulted in a variation in the prediction error rate of 6.2%. The use of data mining technology can improve the efficiency of water conservancy project construction and management, and improve the utilization rate of the project.