標題: Grey self-organizing feature maps
作者: Hu, YC
Chen, RS
Hsu, YT
Tzeng, GH
科技管理研究所
資訊管理與財務金融系 註:原資管所+財金所
Institute of Management of Technology
Department of Information Management and Finance
關鍵字: self-organizing feature maps;grey relation;grey clustering;traveling salesman problem
公開日期: 1-Oct-2002
摘要: In each training iteration of the self-organizing feature maps (SOFM), the adjustable output nodes can be determined by the neighborhood size of the winning node. However, it seems that the SOFM ignores some important information, which is the relationships that actually exist between the input training data and each adjustable output node, in the learning rule. By viewing input data and each adjustable node as a reference sequence and a comparative sequence, respectively, the grey relations between these sequences can be seen. This paper thus incorporates the grey relational coefficient into the learning rule of the SOFM, and a grey clustering method, namely the GSOFM, is proposed. From the simulation results, we can see that the best result of the proposed method applied for analysis of the iris data outperforms those of other known unsupervised neural network models. Furthermore, the proposed method can effectively solve the traveling salesman problem. (C) 2002 Elsevier Science B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/S0925-2312(01)00677-4
http://hdl.handle.net/11536/28473
ISSN: 0925-2312
DOI: 10.1016/S0925-2312(01)00677-4
期刊: NEUROCOMPUTING
Volume: 48
Issue: 
起始頁: 863
結束頁: 877
Appears in Collections:Conferences Paper