Title :
Study on GSOM model based on interval grey number
Author :
Mi, Chuanmin ; Liu, Sifeng ; Xu, Yangzi
Author_Institution :
Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
Abstract :
Considered elements of input node and weight vector are interval grey numbers in Self-organizing Feature Map (SOM), normalized these interval grey numbers, defined the interval grey number Euclidean distance, and proposed Grey SOM (GSOM) model which can solve uncertain problems efficiently. In the end, we studied intelligent clustering of commercial bank off-site regulation empirically using this model. The result showed that: compared with traditional SOM model, GSOM is easy for programming, has a strengthened ability of anti-interference and a higher precision of classification.
Keywords :
bank data processing; grey systems; number theory; pattern classification; pattern clustering; self-organising feature maps; Euclidean distance; GSOM model; commercial bank offsite regulation; data classification; grey self-organizing feature map; intelligent clustering; interval grey number; weight vector; Clustering algorithms; Computer networks; Euclidean distance; Image processing; Intelligent systems; Neural networks; Pattern recognition; Problem-solving; Statistical analysis; Unsupervised learning; Commercial bank off-site regulation; Grey SOM; Interval Grey Number; Model; Neural Networks;
Conference_Titel :
Grey Systems and Intelligent Services, 2007. GSIS 2007. IEEE International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-1294-5
Electronic_ISBN :
978-1-4244-1294-5
DOI :
10.1109/GSIS.2007.4443478
