-
1
-
-
35548968908
-
Data-based process monitoring, process control, and quality improvement: recent developments and applications in steel industry
-
Kano M., Nakagawa Y. Data-based process monitoring, process control, and quality improvement: recent developments and applications in steel industry. Comput. Chem. Eng. 2008, 32:12-24.
-
(2008)
Comput. Chem. Eng.
, vol.32
, pp. 12-24
-
-
Kano, M.1
Nakagawa, Y.2
-
2
-
-
67349089877
-
Data-driven soft sensors in the process industry
-
Kadlec P., Gabrys B., Strandt S. Data-driven soft sensors in the process industry. Comput. Chem. Eng. 2009, 33:795-814.
-
(2009)
Comput. Chem. Eng.
, vol.33
, pp. 795-814
-
-
Kadlec, P.1
Gabrys, B.2
Strandt, S.3
-
4
-
-
33847162850
-
A systematic approach for soft sensor development
-
Lin B., Recke B., Knudsen J.K.H., Jorgensen S.B. A systematic approach for soft sensor development. Comput. Chem. Eng. 2007, 31:419-425.
-
(2007)
Comput. Chem. Eng.
, vol.31
, pp. 419-425
-
-
Lin, B.1
Recke, B.2
Knudsen, J.K.H.3
Jorgensen, S.B.4
-
5
-
-
0033544443
-
Non-linear projection to latent structures revisited (the neural network PLS algorithm)
-
Baffi G., Martin E.B., Morris A.J. Non-linear projection to latent structures revisited (the neural network PLS algorithm). Comput. Chem. Eng. 1999, 23:1293-1307.
-
(1999)
Comput. Chem. Eng.
, vol.23
, pp. 1293-1307
-
-
Baffi, G.1
Martin, E.B.2
Morris, A.J.3
-
6
-
-
33745746500
-
Nonlinear projection to latent structures method and its applications
-
Zhao S.J., Zhang J., Xu Y.M., Xiong Z.H. Nonlinear projection to latent structures method and its applications. Ind. Eng. Chem. Res. 2006, 453:843-3852.
-
(2006)
Ind. Eng. Chem. Res.
, vol.453
, pp. 843-3852
-
-
Zhao, S.J.1
Zhang, J.2
Xu, Y.M.3
Xiong, Z.H.4
-
7
-
-
0034551618
-
Neural networks for the identification and control of blast furnace hot metal quality
-
Radhakrishnan V.R., Mohamed A.R. Neural networks for the identification and control of blast furnace hot metal quality. J. Process Control 2000, 10:509-524.
-
(2000)
J. Process Control
, vol.10
, pp. 509-524
-
-
Radhakrishnan, V.R.1
Mohamed, A.R.2
-
8
-
-
33646775297
-
"Assumed inherent sensor" inversion based ANN dynamic soft-sensing method and its application in erythromycin fermentation process
-
Dai X.Z., Wang W.C., Ding Y.H., Sun Z.Y. "Assumed inherent sensor" inversion based ANN dynamic soft-sensing method and its application in erythromycin fermentation process. Comput. Chem. Eng. 2006, 30:1203-1225.
-
(2006)
Comput. Chem. Eng.
, vol.30
, pp. 1203-1225
-
-
Dai, X.Z.1
Wang, W.C.2
Ding, Y.H.3
Sun, Z.Y.4
-
10
-
-
2342567014
-
Soft sensing modeling based on support vector machine and bayesian model selection
-
Yan W.W., Shao H.H., Wang X.F. Soft sensing modeling based on support vector machine and bayesian model selection. Comput. Chem. Eng. 2004, 28:1489-1498.
-
(2004)
Comput. Chem. Eng.
, vol.28
, pp. 1489-1498
-
-
Yan, W.W.1
Shao, H.H.2
Wang, X.F.3
-
11
-
-
15944390632
-
Weighted support vector machine for quality estimation in the polymerization process
-
Lee D.E., Song J.H., Song S.O., Yoon E.S. Weighted support vector machine for quality estimation in the polymerization process. Ind. Eng. Chem. Res. 2005, 44:2101-2105.
-
(2005)
Ind. Eng. Chem. Res.
, vol.44
, pp. 2101-2105
-
-
Lee, D.E.1
Song, J.H.2
Song, S.O.3
Yoon, E.S.4
-
12
-
-
0031168001
-
Recursive exponentially weighted PLS and its applications to adaptive control and prediction
-
Dayal B.S., MacGregor J.F. Recursive exponentially weighted PLS and its applications to adaptive control and prediction. J. Process Control 1997, 7:169-179.
-
(1997)
J. Process Control
, vol.7
, pp. 169-179
-
-
Dayal, B.S.1
MacGregor, J.F.2
-
13
-
-
0032044750
-
Recursive PLS algorithms for adaptive data modeling
-
Qin S.J. Recursive PLS algorithms for adaptive data modeling. Comput. Chem. Eng. 1998, 22:503-514.
-
(1998)
Comput. Chem. Eng.
, vol.22
, pp. 503-514
-
-
Qin, S.J.1
-
14
-
-
33645417998
-
Online dual updating with recursive PLS model and its application in predicting crystal size of purified terephthalic acid (PTA) process
-
Mu S.J., Zeng Y.Z., Liu R.L., Wu P., Su H.Y., Chu J. Online dual updating with recursive PLS model and its application in predicting crystal size of purified terephthalic acid (PTA) process. J. Process Control 2006, 16:557-566.
-
(2006)
J. Process Control
, vol.16
, pp. 557-566
-
-
Mu, S.J.1
Zeng, Y.Z.2
Liu, R.L.3
Wu, P.4
Su, H.Y.5
Chu, J.6
-
15
-
-
34548395448
-
MIMO soft-sensor model of nutrient content for compound fertilizer based on hybrid modeling technique
-
Fu Y.F., Su H.Y., Chu J.A. MIMO soft-sensor model of nutrient content for compound fertilizer based on hybrid modeling technique. Chin. J. Chem. Eng. 2007, 15:554-559.
-
(2007)
Chin. J. Chem. Eng.
, vol.15
, pp. 554-559
-
-
Fu, Y.F.1
Su, H.Y.2
Chu, J.A.3
-
16
-
-
34147222905
-
On-line soft sensor for polyethylene process with multiple production grades
-
Liu J.L. On-line soft sensor for polyethylene process with multiple production grades. Control Eng. Practice 2007, 15:769-778.
-
(2007)
Control Eng. Practice
, vol.15
, pp. 769-778
-
-
Liu, J.L.1
-
17
-
-
58449118276
-
Development of a new soft sensor method using independent component analysis and partial least squares
-
Kaneko H., Arakawa M., Funatsu K. Development of a new soft sensor method using independent component analysis and partial least squares. AIChE J. 2009, 55:87-98.
-
(2009)
AIChE J.
, vol.55
, pp. 87-98
-
-
Kaneko, H.1
Arakawa, M.2
Funatsu, K.3
-
18
-
-
2942558590
-
A new data-based methodology for nonlinear process Modeling
-
Cheng C., Chiu M.S. A new data-based methodology for nonlinear process Modeling. Chem. Eng. Sci. 2004, 59:2801-2810.
-
(2004)
Chem. Eng. Sci.
, vol.59
, pp. 2801-2810
-
-
Cheng, C.1
Chiu, M.S.2
-
19
-
-
68049143320
-
Soft-sensor development using correlation-based just-in-time modeling
-
Fujiwara K., Kano M., Hasebe S., Takinami A. Soft-sensor development using correlation-based just-in-time modeling. AIChE J. 2009, 55:1754-1765.
-
(2009)
AIChE J.
, vol.55
, pp. 1754-1765
-
-
Fujiwara, K.1
Kano, M.2
Hasebe, S.3
Takinami, A.4
-
20
-
-
35548934238
-
Operation and quality control for chemical plants by soft-sensors
-
(in Japanese)
-
Ookita K. Operation and quality control for chemical plants by soft-sensors. CICSJ Bulletin 2006, 24:31-33. (in Japanese).
-
(2006)
CICSJ Bulletin
, vol.24
, pp. 31-33
-
-
Ookita, K.1
-
21
-
-
79955611348
-
Applicability domains and accuracy of prediction of soft sensor models
-
Kaneko K., Arakawa M., Funatsu K. Applicability domains and accuracy of prediction of soft sensor models. AIChE J. 2011, 57:1506-1513.
-
(2011)
AIChE J.
, vol.57
, pp. 1506-1513
-
-
Kaneko, K.1
Arakawa, M.2
Funatsu, K.3
-
22
-
-
26144466054
-
A review and tutorial discussion of noise and signal-to-noise ratios in analytical spectrometry-I. Fundamental principles of signal-to-noise ratios
-
Alkemade C.T.J., Snelleman W., Boutilier G.D., Pollard B.D., Winefordner J.D., Chester T.L., Omenetto N. A review and tutorial discussion of noise and signal-to-noise ratios in analytical spectrometry-I. Fundamental principles of signal-to-noise ratios. Spectrochim. Acta, Part B 1978, 33:383-399.
-
(1978)
Spectrochim. Acta, Part B
, vol.33
, pp. 383-399
-
-
Alkemade, C.T.J.1
Snelleman, W.2
Boutilier, G.D.3
Pollard, B.D.4
Winefordner, J.D.5
Chester, T.L.6
Omenetto, N.7
-
24
-
-
0000079353
-
Propagation of measurement errors for the validation of predictions obtained by principal component regression and partial least squares
-
Faber K., Kowalski B.R. Propagation of measurement errors for the validation of predictions obtained by principal component regression and partial least squares. J. Chemom. 1997, 11:181-238.
-
(1997)
J. Chemom.
, vol.11
, pp. 181-238
-
-
Faber, K.1
Kowalski, B.R.2
-
25
-
-
21144474350
-
Linear model selection by cross-validation
-
Shao J. Linear model selection by cross-validation. J. Am. Stat. Assoc. 1993, 88:486-494.
-
(1993)
J. Am. Stat. Assoc.
, vol.88
, pp. 486-494
-
-
Shao, J.1
|