水力发电2025，Vol.51Issue(4)：6-11,6.
基于SOM自组织神经网络和K-means方法探究地表水与地下水之间的水力联系
Exploring Hydraulic Connections between Surface Water and Groundwater Based on SOM and K-means Algorithm
摘要
Abstract
Aiming at the hydraulic relationship between surface water and groundwater,the SOM self-organizing neural network and the K-means method are introduced to investigate the hydraulic relationship between surface water and groundwater in a polluted river reach of North China Plain.The analyses show that the water quality of surface water is basically the same with the groundwater quality of 1#,2#,6#and 7#well,meaning a stronger hydraulic connection,and the water quality of surface water is different with the groundwater quality of 3#,8#,9#,10#,12#and 13#well,meaning a weaker hydraulic relationship.The analysis results are basically consistent with the results of traditional systematic clustering method.This research shows that the self-organizing neural network and K-means algorithm can accurately identify the hydraulic relationship between surface water and groundwater,which provides a new solution and technical means for identifying the hydraulic relationship between different aquifers.关键词
地表水/地下水/水力联系/水化学分析/SOM自组织神经网络/K-means/聚类分析Key words
surface water/groundwater/hydraulic connection/water chemistry analysis/SOM self-organizing neural network/K-means/cluster analysis分类
天文与地球科学引用本文复制引用
张大龙,黄勇..基于SOM自组织神经网络和K-means方法探究地表水与地下水之间的水力联系[J].水力发电,2025,51(4):6-11,6.基金项目
国家自然科学基金长江水科学研究联合基金项目(U2240217) （U2240217）
