Process identification using a new component analysis model and particle swarm optimization

Chemometrics and Intelligent Laboratory Systems

Volumn 99, Issue 1, 2009, Pages 19-29

  Fan, Shu Kai S ^a   Lin, Yen ^a   Fan, Chih Min ^a   Wang, Yi Yi ^a  

^a YUAN ZE UNIVERSITY   (Taiwan)

Author keywords

Blind source separation (BSS); Independent component analysis (ICA); Particle swarm optimization (PSO); Principle component analysis (PCA); Process monitoring; Uncorrelated component analysis (UCA)

Indexed keywords

ALGORITHM; ARTICLE; COVARIANCE; ENGINEERING; MATHEMATICAL COMPUTING; MATHEMATICAL PARAMETERS; NOISE; PRIORITY JOURNAL; PROCESS CONTROL; PROCESS DESIGN; PROCESS OPTIMIZATION; STATISTICAL MODEL; VARIANCE;

EID: 70349816783     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chemolab.2009.07.006     Document Type: Article

References (22)

1. Lee J.-M., Yoo C.-K., and Lee I.-B. Statistical process monitoring with independent component-analysis. Journal of Process Control 14 (2004) 467-485
2. del Castillo E. Statistical Process Adjustment for Quality Control (2002), Wiley, New York
3. Montgomery D.C. Introduction to Statistical Quality Control. 5th edition (2005), Wiley, New York
4. Nomikos P., and MacGregor J.F. Monitoring batch processes using multiway principal component-analysis. AIChE Journal 40 (1994) 1361-1375
5. Comon P. Independent component analysis, a new concept?. Signal Processing 36 3 (1994) 287-314
6. Hyvärinen A. Survey on independent component-analysis. Neural Computing Surveys 2 (1999) 94-128
7. Hyvärinen A., and Oja E. Independent component-analysis: algorithms and applications. Neural Networks 13 (2000) 411-430
8. Chang C., Yau S.-F., and Kwok P. Uncorrelated component-analysis for blind source separation. Circuits, Systems, and Signal Processing 18 3 (1999) 225-239
9. Boscolo R., Pan H., and Roychowdhury P. Independent component-analysis based on nonparametric density estimation. IEEE Transactions on Neural Networks 15 (2004) 55-65
10. Lee T. Independent Component-Analysis: Theory and Applications (1998), Kluwer Academic Publishers, Boston
11. FastICA, the Laboratory of Computer and Information Science, Department of Computer Science and Engineering at the Helsinki University of Technology, 2000 (http://www.cis.hut.fi/projects/ica/fastica/).
12. Cardoso J.F. High-order contrasts for independent component-analysis. Neural Computation 11 (1999) 157-192
13. Attias H. Independent factor analysis. Neural Computation 11 (1999) 803-851
14. Vlassis N., and Motomura Y. Efficient source adaptivity in independent component-analysis. IEEE Transactions on Neural Networks 12 (2001) 559-566
15. Bach F.R., and Jordan M.I. Kernel independent component-analysis. Journal of Machine Learning Research 3 (2002) 1-48
16. Myers R.H., and Montgomery D.C. Response Surface Methodology: Process and Product Optimization Using Designed Experiments. 2nd edition (1995), Wiley, New York
17. Kennedy J., and Eberhart R.C. Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks vol. 4 (1995) 1942-1948
18. Courant R. Variational methods for the solution of problems of equilibrium and vibrations. Bulletin of the American Mathematical Society 49 (1943) 1-23
19. Shi Y., and Eberhart R.C. A modified particle swarm optimizer. Proceedings of IEEE International Conference on Evolutionary Computation (1998) 69-73
20. Chatterjee A., and Siarry P. Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization. Computers and Operations Research 33 (2006) 859-871
21. Box G.E.P., Jenkins G.M., and Reinsel G. Time Series Analysis: Forecasting & Control. 3rd edition (1994), Prentice Hall, New York
22. Brockwell P.J., and Davis R.A. Introduction to Time Series and Forecasting. 2nd edition (2002), Springer, New York