A Fusion Clustering Analysis Algorithm and Its Application in Marine Engineering
Clustering analysis is an important approach of data mining, this paper proposed a fusion clustering analysis algorithm based on Coonan network and multi-scale smoothing. Compared with k-means algorithm merged in density-based and integrated clustering analysis algorithm, the new algorithm has more value 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. And also its application in marine engineer has been discussed in the paper. Some analysis results indicated the significant improvement to ship-course design with the new algorithm.
Clustering Data window Kohonen network Multi-scale
Tianzhen Wang Tianhao Tang Hongqiong Huang Funa Zhou
Institute of Electrical & Control Engineering, Shanghai Maritime University, 1550 Pudong Road, Shang Department of electronic engineering, Shanghai Maritime University, 1550 Pudong Road, Shanghai, Chin
国际会议
The 1st International Conference on Risk Analysis and Crisis Response(首届风险分析与危机反应国际学术研讨会)
上海
英文
400-404
2007-09-25（万方平台首次上网日期，不代表论文的发表时间）