The Fuzzy Rough Sets and Algorithm of Fuzzy Rough Clustering Based on Grid
Jiangping Li, Pan Baochang, Wei Yu-ke · 2009
The paper studied a new theory of fuzzy rough sets, and presented a method to approximately estimate objects in a range. It presented an algorithm of fuzzy rough clustering based on grid by the theory. The algorithm extracts condensation points by the theory of fuzzy rough sets, and quarters the data space layer by layer, and softens the edge of the dense block by drawing condensation points in the borders. The tongue diagnosis system is a big, complex one, its data is of great amount and the data cluster has uncertainty. The algorithm has been put into use in rules mining of traditional chinese medicine (TCM) tongue diagnosis system. The application result indicated: The algorithm speeded up cluster by fuzzy grid dividing, saved a lot of time than traditional fuzzy cluster algorithm. The algorithm improved speed, reliability and accuracy of TCM tongue diagnosis, also met the requirements of intellectualization and digitization.