Research On The Soft Computing For The Traditional Chinese Medicine Bace On The NN

Syndrome differentiation in the Traditional Chinese Medicine is an important part of the theory in Traditional Chinese Medicine(TCM).It is a necessary treatment in clinical diagnosis.It is discussed and researched by those famous doctors,who lived in ancient society or live in modern society,and also is the important expressional contents of the medicinal skill.TCM considers the body of man is an inseparable whole and the physiological function and pathological of the body can reflects the natural changes.While the man is ill,TCM can learn the physiological function and pathological changes by the Four Diagnoses in TCM,and treat the disease based on them.The syndrome is the base of the recipe,and the curative effect is influenced by the accurate of the syndrome different indirectly.The beauty of Syndrome differentiation lies in the few diagnostic techniques that accord with the most promising direction in the 21^st century:no pain and no injury. However there is a complex disorder full of contradictions,the Four Diagnoses instantly clarifies the main pathological process.Therefore,it is of great value in both clinic applications and self-diagnosis.However,Traditional Four Diagnosis has inevitable limitations that impede its medical applications.The differentiation of symptoms and signs likes the process of a black-box,the process of the syndrome differentiation is impenetrable.These disadvantages seriously block the more developing of the syndrome differentiation. Moreover some people doubt the science of the TCM.Therefore,it is necessary to build a research on the objectivity and calculability for Syndrome Diagnosis in TCM, which can provide the important theory to the intelligence of the Syndrome Diagnosis and the modernization of the teaching and the scientific research.In this dissertation,the several key technologies of intelligence computing for Eight Principal Syndromes and Zangfu Syndromes in Traditional Chinese Medicine are studied.At first,some neuron models are derived from the concepts of the Artifice Neural Network(ANN),their features and the approximation ability to function are also analyzed.Secondly,the intelligence computing of Syndrome Diagnosis is a premise to establishing a system of automatic diagnosis by the feature of face diagnosis and symptom factors in Traditional Chinese Medicine,whose qualities affect on the performance of face diagnosis and symptom factors.In order to overcome the key difficulties,we design an ANN model according the features of the face diagnosis and symptom factors and the traditional ANN model,which is mostly used in Face Diagnosis and Symptom Factors(FDSFNN).The FDFSNN model mainly includes three parts:first part is the input fore-processing layer;second part is the computing hidden layer for syndrome differencing;last part is the output after-processing layer.The FDSFNN has the memory ability to the sample cases,and can different the syndrome more precisely.Thirdly,the intelligence computing of Syndrome Diagnosis is a premise to establishing a system of automatic diagnosis by the feature of Zangfu Syndromes in Traditional Chinese Medicine,whose qualities affect on the performance of Zangfu Syndromes.In order to overcome the key difficulties,we design an ANN model according the features of the Zangfu Syndromes and the traditional ANN model,which is mostly used in Zangfu Syndromes(ZFSNN).The ZFSNN model mainly includes three parts:first part is the input fore-processing layer;second part is the computing hidden layer for syndrome differencing;last part is the output after-processing layer.The ZFSNN has the memory ability to the sample cases,and can different the syndrome more precisely.At last,the main content of this dissertation is summarized and the related research in the future is prospected in the seventh chapter.