Diagnose model of Parkinson´s disease based on principal component analysis and Sugeno integral

This paper will use principal component analysis and Sugeno integral to structure the model of diagnose Parkinson´s disease. The appropriate value of Sugeno measure is vital to a diagnostic model. The method of using principal component analysis to obtain the sugeno measure is put forward. In this diagnostic model, there are two key factors. One is goodness of fit that the degrees of evidential support for attribute. The other is the importance of attribute itself. The instances of Parkinson´s disease illuminate that the method is effective.