Grey Kmeans algorithm and its application to the analysis of regional competitive ability

Mining and discovering clusters from tremendous data is a useful analysis work for many applications like economics, medicine, engineering, etc. As a widely applied clustering method, Kmeans has the merits of fast running and moderate clustering quality. However, the traditional Euclidean measure has its own inefficiency. In this paper, a new clustering method that integrates the grey relational analysis from grey theory into Kmeans algorithm is proposed to overcome the shortcomings of traditional Kmeans. By applying to the analysis of reginal competitive ability of regions in China, the new algorithm proved to be an effective and efficient method.