The Algorithm of Rough Set-Based Grid Fuzzy Clustering and Its Application and Research in Tongue Diagnosis of Traditional Chinese Medicine

The tongue intelligent diagnosis and inference system of traditional Chinese medicine (TCM) was a complex large-scale system, which data quantity was extremely huge, specially along with long-distance networking diagnosis movement, the data quantity increased dramatically. The system requested fast data search, the fuzzy clustering analysis could solve these difficult problems. This paper on the research cluster analysis basic principle and above the algorithm foundation, utilized one kind of improvement rough set-based grid fuzzy clustering algorithm in data mining for tongue diagnosis system of TCM, and made the grid division first in front of the definition degree of membership function, and formed a data bunch of basic shape, and provided the real parameter information, and participated hereafter degree of membership function definition. The degree of membership function surmounted evaluation influence bunch of shape factor. Algorithm through grid division acceleration cluster process, has overcome shortcoming of big time consumption quantity in the traditional fuzzy clustering algorithm. The application experimental result indicated, the algorithm that the paper have studied enhanced the speed, the reliability and the rate of accuracy in tongue diagnosis system of TCM, and realized the higher intellectualization, the digitized request.