Estimation of Missing Data in Prediction of the Maximum Wind Speed of Typhoon with Probabilistic PCA
In the prediction model for the maximum wind speed of typhoon,the number of the input variables is very large,so the situation of missing data is easy to happen.However,regression analysis can”t deal with this situation.The paper proposes a method to predict missing data based on probabilistic principal component analysis (PPCA),which treats the abnormal data and the predictive variables as missing variables,and it takes Mahalanobis distance to reflect the exact relationship among process variables.The experimental result shows that this method is more flexible than the regression analysis,and it is more accurate.
Probabilistic principal component analysis Missing data reconstruction Mahalanobis distance Software sensor
Hong-Li LI Xin WANG
Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education),Jiangnan University,Wuxi 214122,PR China
国内会议
杭州
英文
1-7
2014-10-18（万方平台首次上网日期，不代表论文的发表时间）