Because of the particularity of the traditional Chinese medicine (TCM), TCM diagnosis is very diverse and has no unified standard. Therefore, the development of TCM was hindered. So in the process of TCM modernization, It is urgently need to solve the standardization and Quantification of qualitative knowledge. Combined with the actual diagnosis cases of children sexual precocity, we'll research intelligent algorithm in the application of expressing knowledge of TCM diagnosis and logical reasoning.This paper has discussed that the fuzzy set theory, the fuzzy clustering analysis and the algorithm of support vector machine are in application of traditional TCM clinical diagnosis of children sexual precocity. At first, we studied how to deal with and express the TCM clinical diagnosis data; Then we put forward the Fuzzy reasoning algorithm to suit for the disease diagnosis and also introduce the modified fuzzy clustering and algorithm of support vector machine.Through the comparison of these three algorithms, we introduce a Synthesis Methodology for improving the accuracy of diagnosis. Automatically diagnosing for 200 patients, the results can be 96% same with what experts diagnosed. So, it states that the algorithm this paper puts forward is effectively feasible. |