Proceeding of the 10th International Congress on Engineering Applications of Neural Networks
巻, 号, ページ
pp. 210-220
出版年月
2007年8月
出版者
和文:
英文:
Publishing Centre Alexander T.E.I. of Thessaloniki
会議名称
和文:
英文:
Engineering Applications of Neural Networks (EANN 2007)
開催地
和文:
英文:
Thessaloniki, Greece
アブストラクト
The batch Self Organizing Map, abbreviated to SOM, is adapted to process imaging for dynamic behavior of aerated agitation vessel, and the application methods are investigated in this article. In the application, the direct imaging by CCD video camera and the PIV technology are adopted. As a result of mapping time-series patterns of velocity distributions to two dimensions, it is shown that generated map and clusters could give process engineers useful information about degree of spatial dispersion of bubbles and about determination of design parameter. The next, two approaches for the data processing in the SOM are investigated to enhance efficiency of pattern analysis: phenomenological approach and statistical approach. As to the statistical approach, it is found that adoption of sigmoid transformation enhances the efficiency of separating the minor difference in the nodes representing the “well-dispersion” patterns and that it would give process engineers useful information about transition of process patterns.
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