A Novel Rough Clustering Algorithm with Fuzzy Weight

For the problem that the classical rough clustering algorithm is not robust to the scale transformation of datasets,by incorporating the idea of fuzzy clustering under the framework of rough clustering,a fuzzy weighing rough clustering algorithm(FWRCA) is proposed using the fuzzy degree of objects in the boundary region as the weights to adjust the centroids.The experiment shows that the proposed algorithm is not only robust to the scale transformation of datasets,but also is less sensitive to partition threshold than rough C-means clustering algorithm(RCMCA) to a certain extent,therefore,performance of the algorithm is better than that of classic C-means rough clustering algorithms such as RCMCA.It can be applied in those fields(such as hydropower engineering science) in which prototype model is the main research mean and large numbers of observation datasets must be transformed proportionally.