Research Andapplication Of Support Vector Machine In Animal Disease Aided Diagnosis System

At present, in the course of the animal disease diagnosis, veterinaries usually make a diagnosis after analyzing and judging the results of instruments examining and the state of animal illness. And it also needs abundant diagnostic experience and pathology knowledge. However, this diagnostic method is usually restricted by some subjective factors. The accuracy of diagnosis is closely related to the level of medical skill. China has a certain number of veterinary experts. But there are a relatively small number of veterinary experts in remote areas, compared with those in the scientific research institutes. Because large-scale livestock breeding farms are usually located in remote areas, it brings that accuracy and timeliness of diseases diagnosis are unsatisfactory. It even causes great economic losses. So people always hope that an intelligent diagnosis method can be found to assist professional exclude people subjective factor and make accurate, objective, timely diagnosis.In nature, animal disease diagnosis is a problem of pattern classification and recognition. It can judge the disease based on symptoms of animal suffered. Support vector machine is a new machine learning, which is developed on the basis of VC dimension of statistical theory and structural risk minimization. It greatly overcomes the limitations of rule-based diagnostic methods SVM has many advantages in dealing with the pattern recognition of limited sample, nonlinear and high dimensional problems. To get the best generalization ability, SVM can find the optimum compromise between the model complexity and its study ability by limit sample information.In this paper, the model of animal disease intelligent diagnosis is designed, which was based on SVM and used to diagnose the cow diseases. The result showed that the method was practical and effective. And this practice provided a new approach for animal disease diagnosis...