The Algorithm of Grid Clustering Based on Fuzzy Rough Set & its Application
Yuke Wei, Jiangping Li, Renhuang Wang · 2008
Traditional Chinese medicine (TCM) tongue diagnosis system is a big, complex one, its data is of great amount and many types, also the data cluster has uncertainty. In this article, the author introduced an advanced algorithm of grid clustering based on fuzzy rough set on the basis of analyzing the theory of fuzzy rough set. The algorithm has been put into use in rules mining of TCM tongue diagnosis system. The first step was grid dividing, to form basis data cluster formation, then provided truly data information in defining membership function. The membership function considered many elements that may influence cluster formation. The algorithm speeded up cluster by fuzzy grid dividing, saved a lot of time than traditional fuzzy cluster algorithm. The application result indicated: the new algorithm improved speed, reliability and accuracy of TCM tongue diagnosis, also met the requirements of intellectualization and digitization.