论文信息 - Dynamic inferential estimation using principal components regression (PCR) - 字舞流文

Dynamic inferential estimation using principal components regression (PCR)

G. Irwin | G. Lightbody | M. Hartnett

[1] Ian T. Jolliffe,et al. Discarding Variables in a Principal Component Analysis. I: Artificial Data , 1972 .

[2] W. Krzanowski. Selection of Variables to Preserve Multivariate Data Structure, Using Principal Components , 1987 .

[3] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[4] Characterization of stationary/mobile phase combinations by using markers : Part 1. Preliminary results for the prediction of reversed-phase retention on various stationary phases , 1988 .

[5] John M. Deane,et al. Testing for redundancy in product quality control test criteria: An application to aviation turbine fuel , 1989 .

[6] G. Dunteman. Principal Components Analysis , 1989 .

[7] Alan J. Miller,et al. Subset Selection in Regression , 1991 .

[8] José Manuel Andrade,et al. Multivariate selection of variables in industrial quality control: Optimizing aviation fuel final control , 1993 .

[9] E. F. Vogel,et al. A plant-wide industrial process control problem , 1993 .

[10] Zbigniew Michalewicz,et al. Genetic algorithms + data structures = evolution programs (2nd, extended ed.) , 1994 .

[11] Christos Georgakis,et al. Disturbance detection and isolation by dynamic principal component analysis , 1995 .

[12] Stephen A. Billings,et al. Model validation tests for multivariable nonlinear models including neural networks , 1995 .