Application And Research Of Fuzzy Competitive Neural Network To Tongue Diagnosis Of Traditional Chinese Medicine

With the international development of Traditional Chinese Medicine (TCM) and the development of global digital information, the digital and standardized study of TCM get more and more important, we must carry out the objective research on four diagnostic methods of TCM: inspection,auscultation and olfaction, inquiry pulse-feeling and palpation, in order to promote the succession and development of TCM. Tongue Diagnosis is one of the most common and the most valuable diagnoses on clinical practice in TCM. With the being perfected computer techniques such as image processing, pattern recognition, artificial intelligence etc., the automation of the Tongue Diagnosis becomes the burgeoning research content. It can avoid some limitations such as non-quantities and uncertainty in the old Tongue Diagnosis, so it has high value of theoretical research and practice. This paper just studies in this direction and the objective of this paper is that points out a new path and direction for the further study of the objective tongue inspection of TCM.Medical diagnosis refers to the process of identifying a disease of a patient by considering his medical history, symptoms and other sign, Diagnosis automation has many advantages. It can meet the needs of the medical service on far way areas where medical experts are in great need of, furthermore it can save much money, relieve patients' pains, keep precious medical experience and data, and bring many benefits to human beings as a result. But the medicine diagnostic system is an extremely complex system. It is very difficult to use the formalized expression. In other words, the using of the general logical inference method hard to attain satisfied effect,therefore it is also difficult to realize the digitization and the automation.Tongue Diagnosis of TCM also is so. Medical diagnosis can be regarded as a non-linear mapping process, so yet can be carried out through the Neural Network. Because of the characteristics, such as classification, studying, memory, associating, calculating, fault-tolerant, real-time quality of the neural network, etc, it is comparatively suitable to adopting the Neural Network and using it as diagnose systematic model.This paper take the Tongue Diagnosis as a background, through merging fuzzy logic inference, neural network control technology, we present an intelligent inference model based on competitive neural network, which has succeeded in imitating the TCM specialist's diagnosis inference. In this model, the use of artificial neural network technology to realize fuzzy inference and realizes the diagnosis with the competition nerve network. This fuzzy control algorithm integrates advantages of both fuzzy logic control and artificial neural network, and the application of competitive neural network enabled the system to have the on-line study ability.The author has mainly completed following two tasks in the paper:1,The application of self-organizing competitive neural network. Self-organizing competitive neural network is an unsupervised learning process. According to beforehand rules and input model, the network modifies the weights continuously until the whole system is order. Self-organizing competitive neural network can make the weights separate mutually through the adjustment of the input weight, and the weights can represent different models in different space, so the input can be clustered by the self-organizing competitive neutral net. In the research process of tongue inspection of TCM, we conductedthe fundamental research about the inference and discrimination of data of Tongue Diagnosis. At the same time,we have produced a concrete simulation experiment. Through the experiment, we can find that the use of competitive neural network can arrive the better classified recognition in the Tongue Diagnosis application.2,The fusion application of Fuzzy logic and neural network technology. Fuzzy logic is suitable for dealingwith unascertained, online and ill-posed problem, but it is lack of the ability of self-learning and self-imaging. Since neural network is applied to fuzzy Inference system, the conventional fuzzy inference system has not only the ability of logic reason and language expression but also the ability of self-learning and self-imaging. Through the fusion technology of neural network and the fuzzy logic, we have studied one new method about TCM's diagnose and inference, which has succeeded in imitating the TCM specialist's diagnosis inference. Simulation and elementary experiment show that the result is testified to be feasible and effective and a kind of new approach for medicine diagnostic process is provided.