-
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.
-
(2008)
Comput. Chem. Eng.
, vol.32
, pp. 12
-
-
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.
-
(2009)
Comput. Chem. Eng.
, vol.33
, pp. 795
-
-
Kadlec, P.1
Gabrys, B.2
Strandt, S.3
-
3
-
-
84872920533
-
Virtual sensing technology in process industries: Trends and challenges revealed by recent industrial applications
-
Kano, M.; Fujiwara, K. Virtual sensing technology in process industries: Trends and challenges revealed by recent industrial applications. J. Chem. Eng. Jpn. 2013, 46, 1-17.
-
(2013)
J. Chem. Eng. Jpn.
, vol.46
, pp. 1-17
-
-
Kano, M.1
Fujiwara, K.2
-
4
-
-
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.
-
(2013)
AIChE J.
, vol.59
, pp. 2339
-
-
Kaneko, H.1
Funatsu, K.2
-
5
-
-
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.
-
(2011)
Comput. Chem. Eng.
, vol.35
, pp. 1
-
-
Kadlec, P.1
Grbic, R.2
Gabrys, B.3
-
6
-
-
0032044750
-
Recursive PLS Algorithms for Adaptive Data Modelling
-
Qin, S. J. Recursive PLS Algorithms for Adaptive Data Modelling. Comput. Chem. Eng. 1998, 22, 503.
-
(1998)
Comput. Chem. Eng.
, vol.22
, pp. 503
-
-
Qin, S.J.1
-
7
-
-
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.
-
(2009)
AIChE J.
, vol.55
, pp. 87
-
-
Kaneko, H.1
Arakawa, M.2
Funatsu, K.3
-
8
-
-
78449310514
-
Development of Self-validating Soft Sensors Using Fast Moving Window Partial Least Squares
-
Liu, J. L.; Chen, D. S.; Shen, J. F. Development of Self-validating Soft Sensors Using Fast Moving Window Partial Least Squares. Ind. Eng. Chem. Res. 2010, 9, 11530.
-
(2010)
Ind. Eng. Chem. Res.
, vol.9
, pp. 11530
-
-
Liu, J.L.1
Chen, D.S.2
Shen, J.F.3
-
9
-
-
84896913551
-
A Localized Adaptive Soft Sensor for Dynamic System Modeling
-
Ni, W. D.; Brown, S. D.; Man, R. L. A Localized Adaptive Soft Sensor for Dynamic System Modeling. Chem. Eng. Sci. 2014, 111, 350.
-
(2014)
Chem. Eng. Sci.
, vol.111
, pp. 350
-
-
Ni, W.D.1
Brown, S.D.2
Man, R.L.3
-
10
-
-
84899518485
-
Industrial PLS Model Variable Selection Using Moving Window Variable Importance in Projection
-
Lu, B.; Castillo, I.; Chiang, L.; Edgar, T. F. Industrial PLS Model Variable Selection Using Moving Window Variable Importance in Projection. Chemom. Intell. Lab. Syst. 2014, 135, 90.
-
(2014)
Chemom. Intell. Lab. Syst.
, vol.135
, pp. 90
-
-
Lu, B.1
Castillo, I.2
Chiang, L.3
Edgar, T.F.4
-
11
-
-
0036639869
-
Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning
-
Schaal, S.; Atkeson, C. G.; Vijayakumar, S. Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning. Appl. Intell. 2002, 17, 49.
-
(2002)
Appl. Intell.
, vol.17
, pp. 49
-
-
Schaal, S.1
Atkeson, C.G.2
Vijayakumar, S.3
-
12
-
-
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.
-
(2004)
Chem. Eng. Sci.
, vol.59
, pp. 2801
-
-
Cheng, C.1
Chiu, M.S.2
-
13
-
-
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.
-
(2009)
AIChE J.
, vol.55
, pp. 1754
-
-
Fujiwara, K.1
Kano, M.2
Hasebe, S.3
Takinami, A.4
-
14
-
-
84863278909
-
Development of Interval Soft Sensors Using Enhanced Just-in-time Learning and Inductive Confidence Predictor
-
Liu, Y. Q.; Huang, D. P.; Li, Y. Development of Interval Soft Sensors Using Enhanced Just-in-time Learning and Inductive Confidence Predictor. Ind. Eng. Chem. Res. 2012, 51, 3356.
-
(2012)
Ind. Eng. Chem. Res.
, vol.51
, pp. 3356
-
-
Liu, Y.Q.1
Huang, D.P.2
Li, Y.3
-
15
-
-
84878409484
-
A SEVA Soft Sensor Method Based on Self-calibration Model and Uncertainty Description Algorithm
-
Liu, Y. Q.; Huang, D. P.; Li, Z. F. A SEVA Soft Sensor Method Based on Self-calibration Model and Uncertainty Description Algorithm. Chemom. Intell. Lab. Syst. 2013, 126, 38.
-
(2013)
Chemom. Intell. Lab. Syst.
, vol.126
, pp. 38
-
-
Liu, Y.Q.1
Huang, D.P.2
Li, Z.F.3
-
16
-
-
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.
-
(2011)
Chemom. Intell. Lab. Syst
, vol.107
, pp. 312
-
-
Kaneko, H.1
Funatsu, K.2
-
17
-
-
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.
-
(2011)
Chemom. Intell. Lab. Syst.
, vol.109
, pp. 197
-
-
Kaneko, H.1
Funatsu, K.2
-
18
-
-
84883140452
-
Adaptive Soft Sensor Model Using Online Support Vector Regression with the Time Variable and Discussion on Appropriate Hyperparameters and Window Size
-
K
-
K 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.
-
(2013)
Comput. Chem. Eng.
, vol.58
, pp. 288
-
-
Kaneko, H.1
Funatsu, K.2
-
19
-
-
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.
-
(2010)
AIChE J.
, vol.57
, pp. 1288
-
-
Kadlec, P.1
Gabrys, B.2
-
20
-
-
84880339799
-
Adaptive Soft Sensor for Online Prediction and Process Monitoring Based on a Mixture of Gaussian Process Models
-
Grbića, R.; Slišković, D.; Kadlec, P. Adaptive Soft Sensor for Online Prediction and Process Monitoring Based on a Mixture of Gaussian Process Models. Comput. Chem. Eng. 2013, 58, 84.
-
(2013)
Comput. Chem. Eng.
, vol.58
, pp. 84
-
-
Grbića, R.1
Slišković, D.2
Kadlec, P.3
-
21
-
-
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.
-
(2012)
Ind. Eng. Chem. Res.
, vol.51
, pp. 13227
-
-
Yu, J.1
-
22
-
-
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.
-
(2012)
Comput. Chem. Eng.
, vol.41
, pp. 134
-
-
Yu, J.1
-
23
-
-
84875311589
-
Automatic Determination Method Based on Cross-validation for Optimal Intervals of Time Difference
-
Kaneko, H.; Funatsu, K. Automatic Determination Method Based on Cross-validation for Optimal Intervals of Time Difference. J. Chem. Eng. Jpn. 2013, 46, 1.
-
(2013)
J. Chem. Eng. Jpn.
, vol.46
, pp. 1
-
-
Kaneko, H.1
Funatsu, K.2
-
24
-
-
84872918863
-
Discussion on Time Difference Models and Intervals of Time Difference for Application of Soft Sensors
-
Kaneko, H.; Funatsu, K. Discussion on Time Difference Models and Intervals of Time Difference for Application of Soft Sensors. Ind. Eng. Chem. Res. 2013, 52, 1322.
-
(2013)
Ind. Eng. Chem. Res.
, vol.52
, pp. 1322
-
-
Kaneko, H.1
Funatsu, K.2
-
25
-
-
0141765796
-
Accurate On-line Support Vector Regression
-
Ma, J.; Theliler, J.; Perkins, S. Accurate On-line Support Vector Regression. Neural Comput. 2003, 15, 2683.
-
(2003)
Neural Comput.
, vol.15
, pp. 2683
-
-
Ma, J.1
Theliler, J.2
Perkins, S.3
-
26
-
-
84903588321
-
Adaptive Soft Sensor Based on Online Support Vector Regression and Bayesian Ensemble Learning for Various States in Chemical Plants
-
Kaneko, H.; Funatsu, K. Adaptive Soft Sensor Based on Online Support Vector Regression and Bayesian Ensemble Learning for Various States in Chemical Plants. Chemom. Intell. Lab. Syst. 2014, 137, 57.
-
(2014)
Chemom. Intell. Lab. Syst.
, vol.137
, pp. 57
-
-
Kaneko, H.1
Funatsu, K.2
-
27
-
-
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.
-
(2010)
Struct. Multidiscip. O.
, vol.40
, pp. 137
-
-
Li, G.1
Aute, V.2
Azarm, S.3
-
28
-
-
0035965476
-
PLS-regression: A Basic Tool of Chemometrics
-
Wold, S.; Sjöström, M.; Eriksson, L. PLS-regression: a Basic Tool of Chemometrics. Chemom. Intell. Lab. Syst. 2001, 58, 109.
-
(2001)
Chemom. Intell. Lab. Syst.
, vol.58
, pp. 109
-
-
Wold, S.1
Sjöström, M.2
Eriksson, L.3
-
29
-
-
0042553279
-
Smoothing and Differentiation of Data by Simplified Least Squares Procedures
-
Savitzky, A.; Golay, M. J. E. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Anal. Chem. 1964, 36, 1627.
-
(1964)
Anal. Chem.
, vol.36
, pp. 1627
-
-
Savitzky, A.1
Golay, M.J.E.2
-
30
-
-
84921674824
-
Chemometrics Calculations with Microsoft Excel (5)
-
in Japanese
-
Yoshimura, N.; Takayanagi, M. Chemometrics Calculations with Microsoft Excel (5), J. Comput. Chem., Jpn. 2012, 11, 149 (in Japanese).
-
(2012)
J. Comput. Chem., Jpn.
, vol.11
, pp. 149
-
-
Yoshimura, N.1
Takayanagi, M.2
|