A Geometry-Based Accelerated Fusion Clustering Algorithm and its Application in Marine Engineering

作者：Wang Tianzhen^*; Liu Yang; Tang Tianhao

来源：International Conference on Advanced Measurement and Test (AMT 2010), 2010-05-15 to 2010-05-16.

DOI：10.4028/www.scientific.net/AMR.108-111.106

• Data mining
• clustering analysis
• k-means plus
• computational complexity

In order to solve the problem in k-means algorithm that inappropriate selection of initial clustering centers often causes clustering in local optimum and the time complexity is too high when handling large amounts of data, a fusion clustering algorithm based on geometry is proposed in this paper. The result of experiments shows this algorithm is better than the traditional k-means and the k-means++ algorithms, with higher quality and faster speed. And at last in this paper, we apply it in marine engineering.

• 出版日期2010
• 单位上海海事大学