Unsupervised optimal fuzzy clustering algorithm based on fuzzy c-means

The unsupervised optimal fuzzy clustering algorithm based on the fuzzy c-means algorithm gathered the advantages of the fuzzy c-means algorithm and the unsupervised optimal clustering algorithm.By changing the number of the clustering c gradually,basing on some measures of the effectiveness,the optimal clustering can be found out without supervising.By improving the measurement of the distance,the clustering can not be influenced by the shape of the class,in order to achieve a higher rate of correct clustering results.The simulation result showed that the new algorithm can not only find out the number of the clustering,but also has a better clustering effect compared to the fuzzy c-means algorithm.