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 Parkinsons 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 Parkinsons disease illuminate that the method is effective.
CAO Xiuming SONG Jinjie ZHANG Caipo
Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology,Tianjin 300384, P.R.China
国际会议
The 30th Chinese Control Conference(第三十届中国控制会议)
烟台
英文
1-5
2011-07-01（万方平台首次上网日期，不代表论文的发表时间）