Title : 
Research and Application of Animal Disease Intelligent Diagnosis Based on Support Vector Machine
         
        
            Author : 
Wan, Long ; Bao, Wenxing
         
        
            Author_Institution : 
Dept. of Comput. Sci. & Eng., North Univ. for Ethnics, Yinchuan, China
         
        
        
        
        
        
        
            Abstract : 
Diagnosing animal disease quickly and accurately has the economic effectiveness. But livestock breeding farms usually have relatively poor condition of disease diagnosis and animal disease cannot be diagnosed quickly and accurately. Traditional diagnostic method is usually restricted by some subjective factors. The accuracy of diagnosis is closely related to the level of medical skill. In order to resolve the rapid and accurate diagnosis of animal disease, this paper put forward a model of animal disease intelligent diagnosis which was based on support vector machine (SVM). In the model, the digital data of animal disease symptoms are taken as inputs of the disease classifier and used the classifier of the model to classify (diagnose) the sheep diseases. The results showed that the model is able to carry out animal diseases diagnosis more accurately, rapidly and have good predicality on the condition of small samples and provide a new approach for animal disease diagnosis.
         
        
            Keywords : 
biology computing; learning (artificial intelligence); support vector machines; animal disease intelligent diagnosis; animal disease symptoms; digital data; machine learning; sheep diseases; support vector machine; Agriculture; Animals; Competitive intelligence; Computational intelligence; Diseases; Machine intelligence; Machine learning; Medical diagnostic imaging; Support vector machine classification; Support vector machines; Animal disease; Intelligent diagnosis; SVM;
         
        
        
        
            Conference_Titel : 
Computational Intelligence and Security, 2009. CIS '09. International Conference on
         
        
            Conference_Location : 
Beijing
         
        
            Print_ISBN : 
978-1-4244-5411-2
         
        
        
            DOI : 
10.1109/CIS.2009.199