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
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;
Conference_Titel :
Control and Automation, 2005. ICCA '05. International Conference on
Print_ISBN :
0-7803-9137-3
DOI :
10.1109/ICCA.2005.1528185