Estimation of rotation ambiguity in multivariate curve resolution with charged particle swarm optimization (cPSO-MCR)

Journal of Chemometrics

Volumn 28, Issue 10, 2014, Pages 727-739

  Skvortsov, Alexey N ^a,b  

^a PETER THE GREAT ST PETERSBURG POLYTECHNIC UNIVERSITY   (Russian Federation)

^b INSTITUTE OF CYTOLOGY   (Russian Federation)

Author keywords

Constrained least squares; Metaheuristics; Multivariate curve resolution; Particle swarm optimization; Rotation ambiguity

Indexed keywords

CONSTRAINED OPTIMIZATION; CURVE FITTING; PARTICLE SWARM OPTIMIZATION (PSO);

CONCENTRATION PROFILES; CONSTRAINED LEAST SQUARES; FEASIBLE SOLUTION; METAHEURISTIC; MULTIVARIATE CURVE RESOLUTION; PARTICLE SWARM; PARTICLE SWARM OPTIMIZATION; ROTATION AMBIGUITY; SPECTRA PROFILES; SWARM OPTIMIZATION;

CHARGED PARTICLES;

EID: 84919328869     PISSN: 08869383     EISSN: 1099128X     Source Type: Journal    
DOI: 10.1002/cem.2663     Document Type: Article

References (30)

1. Wallace RM Analysis of absorption spectra of multicomponent systems. Anal. Chem. 1960; 64: 899-901.
2. Lawton WH Sylvestre EA Self modeling curve resolution. Technometrics 1971; 13: 617-633.
3. de Juan A Tauler R Multivariate curve resolution (MCR) from 2000: progress in concepts and applications. Crit. Rev. Anal. Chem. 2006; 36: 163-176.
4. Ruckebusch C Blanchet L Multivariate curve resolution: a review of advanced and tailored applications and challenges. Anal. Chim. Acta 2013; 765: 28-36.
5. Borgen OS Kowalski BR An extension of the multivariate component-resolution method to three components. Anal. Chim. Acta 1985; 174: 1-26.
6. Kantorovich LV Mathematical methods of organizing and planning production. Manag. Sci. 1939; 6: 366-422.
7. Blanchet L, Ruckebusch C, Huvenne J-P de Juan A Focus on the potential of hybrid hard- and soft-MCR-ALS in time resolved spectroscopy. J. Chemometr. 2008; 22: 666-673.
8. Rajkó R Studies on the adaptability of different Borgen norms applied in self-modeling curve resolution (SMCR) method. J. Chemometr. 2009; 23: 265-274.
9. Rajkó R István K Analytical solution for determining feasible regions of self-modeling curve resolution (SMCR) method based on computational geometry. J. Chemometr. 2005; 19: 448-463.
10. Abdollahi H, Maeder M Tauler R Calculation and meaning of feasible band boundaries in multivariate curve resolution of a two-component system. Anal. Chem. 2009; 81: 2115-2122.
11. Abdollahi H Tauler R Uniqueness and rotation ambiguities in multivariate curve resolution methods. Chemometr. Intell. Lab. Syst. 2011; 108: 100-111.
12. Jaumot J Tauler R MCR-BANDS: a user friendly MATLAB program for the evaluation of rotation ambiguities in multivariate curve resolution. Chemometr. Intell. Lab. Syst. 2010; 103: 96-107.
13. Tauler R Application of non-linear optimization methods to the estimation of multivariate curve resolution solutions and of their feasible band boundaries in the investigation of two chemical and environmental simulated data sets. Anal. Chim. Acta 2007; 595: 289-298.
14. Golshan A, Abdollahi H Maeder M The resolution of rotational ambiguity for three component systems. Anal. Chem. 2011; 83: 836-841.
15. Golshan A, Maeder M Abdollahi H Determination and visualization of rotational ambiguity in four-component systems. Anal. Chim. Acta 2013; 796: 20-26.
16. Hopke PK, Alpert DJ Roscoe BA FANTASIA - a program for target transformation factor analysis to apportion sources in environmental samples. Comput. Chem. 1983; 7: 149-155.
17. Mason C, Maeder M Whitson A Resolving factor analysis. Anal. Chem. 2001; 73: 1587-1594.
18. Jaumot J, Gargallo R, de Juan A Tauler R An user friendly interface for MCR-ALS: a new tool for Multivariate Curve Resolution in MATLAB. Chemometr. Intell. Lab. Syst. 2005; 76: 101-110.
19. Blum C Roli A Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput. Surv. 2003; 35: 268-308.
20. Kennedy J, Eberhart R. Particle swarm optimization. Proceedings of the Fourth IEEE International Conference on Neural Networks, Perth, Australia, 1995; 1942-1948.
21. Shi Y, Eberhart RC. A modified particle swarm optimizer. Evolutionary Computation Proceedings, IEEE World Congress on Computational Intelligence, Anchorage, Alaska, 1998; 69-73.
22. Engelbrecht AP. Fundamentals of Computational Swarm Intelligence, John Wiley: New York, 2005.
23. Shinzawa H, Jiang J-H, Iwahashi M, Nodad I Ozaki Y Self-modeling curve resolution (SMCR) by particle swarm optimization (PSO). Anal. Chim. Acta 2007; 595: 275-281.
24. Parastar H, Ebrahimi-Najafabadi H Jalali-Heravi M Multivariate curve resolution-particle swarm optimization: a high-throughput approach to exploit pure information from multi-component hyphenated chromatographic signals. Anal. Chim. Acta 2013; 772: 16-25.
25. Blackwell TM, Bentley PJ. Dynamic search with charged swarms. Proceedings of the Genetic and Evolutionary Computation Conference, San Francisco, 2002; 19-26.
26. Björck A. Numerical Methods for Least Squares Problems, Society for Industrial and Applied Mathematics: Philadelphia, 1996.
27. Pedersen MEH Chipperfield AJ Simplifying particle swarm optimization. Appl. Soft Comput. 2010; 10: 618-628.
28. Jin J-M. Theory and Computation of Electromagnetic Fields, Wiley-IEEE Press: New Jersey, 2010.
29. Draper NR Smith H. Applied Regression Analysis, Wiley Series in Probability and Statistics, (3rd edn) John Wiley: New York, 1989.
30. Amrhein M, Srinivasan B, Bonvin D Schumacher MM On the rank deficiency and rank augmentation of the spectral measurement matrix. Chemometr. Intell. Lab. Syst. 1996; 33: 17-33.