-
1
-
-
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
-
2
-
-
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
-
3
-
-
79954599740
-
Local learning-based adaptive soft sensor for catalyst activation prediction
-
Kadlec P, Gabrys B. Local learning-based adaptive soft sensor for catalyst activation prediction, AIChE J. 2010;57:1288-1301.
-
(2010)
AIChE J.
, vol.57
, pp. 1288-1301
-
-
Kadlec, P.1
Gabrys, B.2
-
4
-
-
0032044750
-
Recursive PLS algorithms for adaptive data modeling
-
Qin SJ. 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
-
5
-
-
2942558590
-
A new data-based methodology for nonlinear process modeling
-
Cheng C, Chiu MS. 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
-
6
-
-
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
-
7
-
-
0036639869
-
Scalable techniques from onparametric statistics for real time robot learning
-
Schaal S, Atkeson CG, Vijayakumar S. Scalable techniques from onparametric statistics for real time robot learning. Appl Intell. 2002;17:49-60.
-
(2002)
Appl Intell.
, vol.17
, pp. 49-60
-
-
Schaal, S.1
Atkeson, C.G.2
Vijayakumar, S.3
-
8
-
-
79959784751
-
Maintenance-free soft sensor models with time difference of process variables
-
Kaneko H, Funatsu K. Maintenance-free soft sensor models with time difference of process variables. Chemom Intell Lab Syst. 2011;107:312-317.
-
(2011)
Chemom Intell Lab Syst.
, vol.107
, pp. 312-317
-
-
Kaneko, H.1
Funatsu, K.2
-
9
-
-
80055094175
-
A soft sensor method based on values predicted from multiple intervals of time difference for improvement and estimation of prediction accuracy
-
Kaneko H, Funatsu K. A soft sensor method based on values predicted from multiple intervals of time difference for improvement and estimation of prediction accuracy. Chemom Intell Lab Syst. 2011;109:197-206.
-
(2011)
Chemom Intell Lab Syst.
, vol.109
, pp. 197-206
-
-
Kaneko, H.1
Funatsu, K.2
-
10
-
-
80052838846
-
Development of soft sensor models based on time difference of process variables with accounting for nonlinear relationship
-
Kaneko H, Funatsu K. Development of soft sensor models based on time difference of process variables with accounting for nonlinear relationship. Ind Eng Chem Res. 2011;50:10643-10651.
-
(2011)
Ind Eng Chem Res.
, vol.50
, pp. 10643-10651
-
-
Kaneko, H.1
Funatsu, K.2
-
11
-
-
78649468188
-
Review of adaptation mechanisms for data-driven soft sensors
-
Kadlec P, Grbic R, Gabrys B. Review of adaptation mechanisms for data-driven soft sensors. Comput Chem Eng. 2011;35:1-24.
-
(2011)
Comput Chem Eng.
, vol.35
, pp. 1-24
-
-
Kadlec, P.1
Grbic, R.2
Gabrys, B.3
-
12
-
-
84868224530
-
Multiway gaussian mixture model based adaptive kernel partial least squares regression method for soft sensor estimation and reliable quality prediction of nonlinear multiphase batch processes
-
Yu J. Multiway gaussian mixture model based adaptive kernel partial least squares regression method for soft sensor estimation and reliable quality prediction of nonlinear multiphase batch processes. Ind Eng Chem Res. 2012;51:13227-13237.
-
(2012)
Ind Eng Chem Res.
, vol.51
, pp. 13227-13237
-
-
Yu, J.1
-
13
-
-
84859392648
-
A Bayesian inference based two-stage support vector regression framework for soft sensor development in batch bioprocesses
-
Yu J. A Bayesian inference based two-stage support vector regression framework for soft sensor development in batch bioprocesses. Comput Chem Eng. 2012;41:134-144.
-
(2012)
Comput Chem Eng.
, vol.41
, pp. 134-144
-
-
Yu, J.1
-
14
-
-
84861955990
-
Development of a model selection method based on reliability of a soft sensor model
-
Okada T, Kaneko H, Funatsu K. Development of a model selection method based on reliability of a soft sensor model. Songklanakarin J Sci Technol. 2012;34:217-222.
-
(2012)
Songklanakarin J Sci Technol.
, vol.34
, pp. 217-222
-
-
Okada, T.1
Kaneko, H.2
Funatsu, K.3
-
15
-
-
84879309312
-
Classification of the degradation of soft sensor models and discussion on adaptive models
-
Kaneko H, Funatsu K. Classification of the degradation of soft sensor models and discussion on adaptive models. AIChE J. 2013;59:2339-2347.
-
(2013)
AIChE J.
, vol.59
, pp. 2339-2347
-
-
Kaneko, H.1
Funatsu, K.2
-
16
-
-
0141765796
-
Accurate on-line support vector regression
-
Ma J, Theliler J, Perkins S. Accurate on-line support vector regression. Neural Comput. 2003;15:2683-2703.
-
(2003)
Neural Comput.
, vol.15
, pp. 2683-2703
-
-
Ma, J.1
Theliler, J.2
Perkins, S.3
-
18
-
-
84883140452
-
Adaptive soft sensor model using online support vector regression with the time variable and discussion on appropriate hyperparameters and window size
-
Kaneko H, Funatsu K, Adaptive soft sensor model using online support vector regression with the time variable and discussion on appropriate hyperparameters and window size. Comput Chem Eng. 2013;58:288-297.
-
(2013)
Comput Chem Eng.
, vol.58
, pp. 288-297
-
-
Kaneko, H.1
Funatsu, K.2
-
19
-
-
33846087392
-
Online trained support vector machines-based generalized predictive control of non-linear systems
-
Iplikci, S. Online trained support vector machines-based generalized predictive control of non-linear systems. Int J Adapt Control Signal Process. 2006;20:599-621.
-
(2006)
Int J Adapt Control Signal Process.
, vol.20
, pp. 599-621
-
-
Iplikci, S.1
-
20
-
-
58349104545
-
Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions
-
Neto MC, Jeong YS, Jeong MK, Han LD. Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions. Expert Syst Appl. 2009;36:6164-6173.
-
(2009)
Expert Syst Appl.
, vol.36
, pp. 6164-6173
-
-
Neto, M.C.1
Jeong, Y.S.2
Jeong, M.K.3
Han, L.D.4
-
21
-
-
68549107645
-
Forecasting respiratory motion with accurate online support vector regression
-
Ernst F, Schweikard A. Forecasting respiratory motion with accurate online support vector regression. Int J CARS. 2009;4:439-447.
-
(2009)
Int J CARS.
, vol.4
, pp. 439-447
-
-
Ernst, F.1
Schweikard, A.2
-
23
-
-
84892435172
-
-
Online Support Vector Regression. Software available at (accessed December 14, 2013).
-
Parrella F. Online Support Vector Regression. Software available at http://onlinesvr.altervista.org/ (accessed December 14, 2013).
-
-
-
Parrella, F.1
-
25
-
-
81755166220
-
Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection
-
Kim S, Kano M, Nakagawa H, Hasebe S. Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection. Int J Pharm. 2011;421:269-274.
-
(2011)
Int J Pharm.
, vol.421
, pp. 269-274
-
-
Kim, S.1
Kano, M.2
Nakagawa, H.3
Hasebe, S.4
-
26
-
-
72149085992
-
An accumulative error based adaptive design of experiments for offline metamodeling
-
Li G, Aute V, Azarm S. An accumulative error based adaptive design of experiments for offline metamodeling. Struct Multidiscip O. 2010;40:137-155.
-
(2010)
Struct Multidiscip O.
, vol.40
, pp. 137-155
-
-
Li, G.1
Aute, V.2
Azarm, S.3
-
27
-
-
0026169941
-
On-line inference of polymer properties in an industrial polyethylene reactor
-
McAuley KB, MacGregor JF. On-line inference of polymer properties in an industrial polyethylene reactor. AIChE J. 1991;37:825-835.
-
(1991)
AIChE J.
, vol.37
, pp. 825-835
-
-
McAuley, K.B.1
MacGregor, J.F.2
-
28
-
-
0033874542
-
Quality control of polymer production processes
-
Ohshima M, Tanigaki M. Quality control of polymer production processes. J Process Control. 2000;10:135-148.
-
(2000)
J Process Control.
, vol.10
, pp. 135-148
-
-
Ohshima, M.1
Tanigaki, M.2
-
29
-
-
35548955182
-
Prediction of the melt index in a high-density polyethylene process
-
Lee EH, Kim TY, Yeo, YK. Prediction of the melt index in a high-density polyethylene process. J Chem Eng Jpn. 2007;40:840-846.
-
(2007)
J Chem Eng Jpn.
, vol.40
, pp. 840-846
-
-
Lee, E.H.1
Kim, T.Y.2
Yeo, Y.K.3
-
30
-
-
11144244974
-
Prediction of pellet properties for an industrial bimodal high-density polyethylene process with Ziegler-Natta catalysts
-
Oh SJ, Lee J, Park S. Prediction of pellet properties for an industrial bimodal high-density polyethylene process with Ziegler-Natta catalysts. Ind Eng Chem Res. 2005;44:8-20.
-
(2005)
Ind Eng Chem Res.
, vol.44
, pp. 8-20
-
-
Oh, S.J.1
Lee, J.2
Park, S.3
-
31
-
-
79955476246
-
Novel soft sensor method for detecting completion of transition in industrial polymer processes
-
Kaneko H, Arakawa M, Funatsu K. Novel soft sensor method for detecting completion of transition in industrial polymer processes. Comput Chem Eng. 2011;35:1135-1142.
-
(2011)
Comput Chem Eng.
, vol.35
, pp. 1135-1142
-
-
Kaneko, H.1
Arakawa, M.2
Funatsu, K.3
|