An approach to parameters estimation of a chromatography model using a clustering genetic algorithm based inverse model-Reference-Cited by-同舟云学术

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An approach to parameters estimation of a chromatography model using a clustering genetic algorithm based inverse model

Published:2010-08-04 Issue:5 Volume:15 Page:963-973
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Irizar Mesa Mirtha,Llanes-Santiago Orestes,Herrera Fernández Francisco,Curbelo Rodríguez David,Da Silva Neto Antônio José,Câmara Leôncio Diógenes T.

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-010-0638-3.pdf

Reference48 articles.

1. Altenhöner U, Meurer M, Strube J, Schmidt-Traub H (1997) Parameter estimation for the simulation of liquid chromatography. J Chromatogr 769:59–69

2. Andrés-Toro B, Besada-Portas E, Fernández-Blanco P, López-Orozco J, Girón-Sierra J (2002) Multiobjective optimization of dynamic processes by evolutionary methods. In: Proceedings of the 15th IFAC World Congress on Automatic Control, pp 342–348. Barcelona, Spain

3. Angelov P, Guthke R (1997) A ga-based approach to optimization of bioprocesses described by fuzzy rules. J Bioprocess Eng 16:299–301

4. Au W, Chan K, Yao X (2003) A novel evolutionary data mining algorithm with applications to churn prediction. IEEE Trans Evol Comput 7(6):532–545

5. Back T (1997) Handbook of evolutionary computation. Oxford University Press, Oxford

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4. Tuning Evolutionary Multiobjective Optimization for Closed-Loop Estimation of Chromatographic Operating Conditions;Parallel Problem Solving from Nature – PPSN XIII;2014

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