DocumentCode
2346134
Title
An ANN-based clustering analysis algorithm with dynamic data window
Author
Tianhao, Tang ; Tianzhen, Wang
Author_Institution
Electr. & Control Eng. Inst., Shanghai Maritime Univ., China
Volume
1
fYear
2005
fDate
26-29 June 2005
Firstpage
581
Abstract
Clustering analysis is an important approach of data mining. This paper presents an ANN-based clustering analysis algorithm with dynamic data window (DDW). Comparing with k-means algorithm merged in density-based and integrated clustering analysis algorithm, the new clustering analysis algorithm based on artificial neural networks and combining with DDW has more valuable in data mining. This algorithm can immensely avoid the effect on accumulation points from boundary points, and can automatically find representative accumulation points in all kings of shapes. Furthermore its applications in CIS will be discussed in the paper. Some analysis results show the significant improvement to ship-routing design with the clustering analysis algorithm based on ANN and DDW in database of CIS.
Keywords
data mining; neural nets; pattern clustering; artificial neural networks; clustering analysis; data mining; dynamic data window; k-means algorithm; Algorithm design and analysis; Artificial neural networks; Clustering algorithms; Control engineering; Data mining; Geographic Information Systems; Heuristic algorithms; Partitioning algorithms; Shape; Visual databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation, 2005. ICCA '05. International Conference on
Print_ISBN
0-7803-9137-3
Type
conf
DOI
10.1109/ICCA.2005.1528185
Filename
1528185
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