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Proceedings Paper

ART2 neural network clustering for hierarchical simulation
Author(s): Yang Guo; Xianghong Yin; Weibo Gong
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Paper Abstract

In this paper, we propose to employ the ART2 neural network to cluster the high dimensional vectors for the preservation of statistics in hierarchical simulation. The experiments show that ART2 serves this purpose quite well. The inter- and intra-cluster difference calculated indicated that ART2 clusters data according to Euclidean distance 'approximately'. The numerical results also indicate that the 'vigilance parameter' determines the degree of similarity of vectors in the same cluster by controlling the entire variation.

Paper Details

Date Published: 24 August 1998
PDF: 14 pages
Proc. SPIE 3369, Enabling Technology for Simulation Science II, (24 August 1998); doi: 10.1117/12.319351
Show Author Affiliations
Yang Guo, Univ. of Massachusetts/Amherst (United States)
Xianghong Yin, Univ. of Massachusetts/Amherst (United States)
Weibo Gong, Univ. of Massachusetts/Amherst (United States)


Published in SPIE Proceedings Vol. 3369:
Enabling Technology for Simulation Science II
Alex F. Sisti, Editor(s)

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