A Geometry-Based Accelerated Fusion Clustering Algorithm and its Application in Marine Engineering
Tian Zhen Wang, Yang Liu, Tian Hao Tang · Advanced materials research · 2010
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.