Title :
Cluster Analysis of Listed Company Solvency Based on the SOM
Author :
Yun Lin ; Jie Wang
Author_Institution :
Sch. of Manage., Capital Normal Univ., Beijing, China
Abstract :
Enterprise managers should master the debt risk in order to make the right decision. SOM (Self-Organizing Maps) is a type of artificial neural network trained by unsupervised learning. First, the paper improves the neighborhood function of SOM network. Then, this paper uses the improved SOM network to cluster 24 steel listed companies´ solvency. The sort of solvency will offer solution for operators to find insufficiencies for enterprise development.
Keywords :
data analysis; manufacturing data processing; pattern clustering; self-organising feature maps; steel industry; SOM network neighborhood function; artificial neural network; cluster analysis; enterprise development; listed company solvency; self-organizing maps; steel company; unsupervised learning; Companies; Data mining; Indexes; Neural networks; Neurons; Profitability; Steel; Cluster analysis; Self-Organized Map; Solvency;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on
Print_ISBN :
978-1-4799-7004-9
DOI :
10.1109/ISCID.2014.225
