Intelligent Data Pretreatment Based on Principal Component Analysis and Fuzzy C-means Clustering in Flotation Process
会议名称：《第二十六届中国控制会议》
会议日期：2007年
学科分类：12[管理学] 0810[工学-信息与通信工程] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0835[工学-软件工程] 081002[工学-信号与信息处理] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by National Nature Science Foundation under Grant 60474058
关 键 词：Data Pretreatment Fuzzy C-means Clustering(FCM) Principal Component Analysis(PCA) Flotation Process Radial Basis Function(RBF)
摘 要：A data pretreatment algorithm based on principal component analysis and fuzzy c-means clustering for flotation process is proposed in this *** regression of clustering centers gained by fuzzy c-means clustering algorithm is in-troduced to carry through data *** process prior knowledge and principal component analysis method are used to reduce dimensions of input vectors and to choose the secondary *** the paper uses radial basis function neural network（RBFNN）to set up an inferential estimation model of quality indexes of flotation process aiming at principal com-ponent *** simulation results show that this inference estimation strategy has high predictive accuracy in flotation process.