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Issue:Development of a Generalized Net for Comparison of Different Models Obtained using Metaheuristic Algorithms

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Title of paper: Development of a Generalized Net for Comparison of Different Models Obtained using Metaheuristic Algorithms
Author(s):
Dimitar Dimitrov
Faculty of Mathematics and Informatics, Sofia University, 5 James Bourchier Str., Sofia, Bulgaria
dgdimitrov@fmi.uni-sofia.bg
Olympia Roeva
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. G. Bonchev Str., 1113 Sofia, Bulgaria
olympia@biomed.bas.bg
Published in: "Issues in Intuitionistic Fuzzy Sets and Generalized Nets", Volume 13 (2017), pages 109-118
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Abstract: The present paper proposes a developed generalized net model that compares different mathematical models of the process of E. coli fedbatch cultivation. A system of four ordinary differential equations describes the main variables of the considered cultivation process. For the purposes of model simulation, we use the software package GNLite. The GN model compares the simulated performance of the proposed set of mathematical models and selects the best performing one one the basis of a predefined criterion. During the simulation, GNLite calls the Matlab software environment to solve the process model, presented as a system of nonlinear differential equations, and plots the dynamics of the main process variables' of the model that has been computed to perform best.
Keywords: Generalized net, GNLite, GNTicker, GN IDE, E. coli, Fed-batch cultivation, Mathematical models.
References:
  1. Atanassov, K., On Generalized Nets Theory. Sofia, “Prof. M. Drinov” Acad. Publ. House, 2007.
  2. Dimitrov, D. G., Integration of the Generalized Nets Simulator GNTicker with MATLAB, Annual of "Informatics" Section, Union of Scientists in Bulgaria, Vol. 4, 2011, 49-52, (In Bulgarian).
  3. Dimitrov, D. G., & Roeva, O. Comparison of Different Mathematical Models of an E. coli Fed-batch Cultivation Process Using Generalized Net Model, Proc. of the 13th Int. Workshop on Generalized Nets, 29 October 2012, London, UK, 2012, 15-23.
  4. Dimitrov, D. G., Software Products Implementing Generalized Nets, Annual of "Informatics" Section, Union of Scientists in Bulgaria, Vol. 3, 2010, 37–50, (In Bulgarian).
  5. Kosev, K., Trenkova, T., & Roeva, O. Tabu Search for Parameter Identification of an Fermentation Process Model, J. of Int. Scientific Publication: Materials, Methods & Technologies, Vol. 6, No 2, 2012, 457-464.
  6. Krawczak, M., A Novel Modeling Methodology: Generalized Nets, In: Artificial Intelligence and Soft Computing, A. Cader, L. Rutkowski, R. Tadeusiewicz and J. Zurada, Eds., Publishing House Exit, Warsaw, 2006, 1160-1168.
  7. Krawczak, M., Generalized net models of MLNN learning algorithms, Lecture Notes in Computer Science, Vol. 2, No 3697, 2005, 25-30.
  8. Roeva, O., Optimization of E. coli Cultivation Model Parameters using Firefly Algorithm, Int. J. Bioautomation, Vol. 16, No 1, 2012, 23-32.
  9. Roeva, O., Parameter Estimation of a Monod-type Model based on Genetic Algorithms and Sensitivity Analysis, Lecture Notes on Computer Science, Springer-Verlag Berlin Heidelberg, Vol. 4818, 2008, 601-608.
  10. Shannon, A., Roeva, O., Pencheva, T., & Atanassov, K. Generalized Nets Modelling of Biotechnological Processes, Prof. M. Drinov Academic Publishing House, Sofia, 2004.
  11. Trifonov, T., Georgiev, K., & Atanassov, K. Software for modelling with generalized nets, Issues in Intuitionistic Fuzzy Sets and Generalized Nets, Wydawnictwo Wsisiz, Warsaw, Vol. 6, 2008, 96-110.
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