%0 Dataset
%T Five influencing factor datasets: water level height difference, overburden thickness, permeability coefficient, porosity ratio and compressibility coefficient of Yangxin Dry Dike in the Yangtze River
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/c6b101ae-8bae-46fb-b05f-c849d92f3373
%W NCDC
%R 10.12072/ncdc.nhri.db6793.2025
%A Lu Minggui
%K Levee seepage;machine learning
%X The dataset contains 73 sample data sets from the Yangxin embankment of the Yangtze River. Through grey relational analysis, five key influencing factors were extracted: water level height difference, cover layer thickness, permeability coefficient, porosity, and compressibility coefficient. After analysis, the dataset records the main factors influencing embankment seepage, providing crucial data for embankment safety assessment, flood control model construction, and training and validation of machine learning algorithms. This dataset can be widely applied in the field of water conservancy engineering, promoting the development of related research and practical applications.