Font Size: a A A

Research On The Identification Of Body Constitutional Types In Chinese Medicine Based On BP Neural Network

Posted on:2015-02-28Degree:MasterType:Thesis
Country:ChinaCandidate:L N BaiFull Text:PDF
GTID:2284330467955353Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
During the period of "11th five-year plan", traditional Chinese medicine informatizationconstruction has made remarkable results adapting to the medical and health system reformand the development of Chinese medicine career, and has preliminary establishedTCMclinical information sharing platform and development platform. Facing the goldenopportunity of development, the informatization construction of traditional Chinese medicineis ready, all-round development.Science and technology is productivity.All walks of life developrapidly with informationtechnology. But the development of traditional Chinese medicineis relatively slow for itsspecial way of inheritance and development.Using the power of science and technology todevelop and equip the traditional Chinese medicineundoubtedly can effectively improve thequality and service level of traditional Chinese medicine.With the improvement of people’s living quality, health care and "Preventing illness"attract more and more people’s attention. At the end of2009, identification of TCM wasincorporated into the national basic public health service specification. Through physicalidentification, individuals could understand what physical type theyare, and then according tothe diseases that the constitution was susceptible toadjust the dietof personal daily life. Theeffect of TCM identification is to reduce risk of disease by understanding the disease. Thejudgement of constitution typeprovides the "cure not ill" ways and meansfor the large crowd,which can make the most people out of sub-health state and benefit more people.According to the characteristics of the identification of traditional Chinesemedicineconstitution,thispaper constructsthe BP neural network model that applicable to Chinesemedicine constitution identification,by using the theory of BP neural network.Theauthorconstructed TCM constitution identification system based on BP neuralnetworkbased on the research of the network structure design and learning algorithmby usingthe Visual Basic language. Through comparing the result of system test with the traditionalChinese medicine experts,the author’s analysis could verify that appliedthe neural network tothe identification of TCM constitution was validity, rationality and superiority. The system ofTCM constitution identification is completed in solving the problem of limited resources oftraditional Chinese medicine, at the same time it can make the medicine more widely spreadin China, and better inheritance and development.This paper first analyzes thebackground of topic research and the significance ofphysical identification of traditional Chinese medicine, and briefly introduces the maincontent and the technical routeabout this paper; After that,analyzes the present situationaboutthe identification of TCM constitution, and put forward the corresponding solutionsbased on the existing problems out of the analysis on the identification of TCMconstitution;Then, the neural network theory is briefly introduced and BP neural network theory is expounded in detail. The BP neural networkthat applied to the identification ofTCMconstitution is suitability, and based that structured BP neural network model applied toidentification of TCM constitution, and then, develop the system of identification of TCMconstitution based on BP neural network model. Throughindependent establishingthesystemto test and verify that the BP neural network applied to the constitution of traditionalChinese medicine is rationality, applicability and practicability.Finally, this paper summarizethecontent and makes application prospectof the identification system of TCM constitution.
Keywords/Search Tags:Artificial neural network, BP neural network, Body ConstitutionalTypes, Identification
PDF Full Text Request
Related items