| Title of paper:
|
InterCriteria Analysis results based on different number of objects
|
| Author(s):
|
| Dafina Zoteva
|
| Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. G. Bonchev Str., Sofia 1113, Bulgaria
|
| dafy.zoteva@gmail.com
|
| Olympia Roeva
|
| Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. G. Bonchev Str., Sofia 1113, Bulgaria
|
| olympia@biomed.bas.bg
|
|
| Published in:
|
Notes on Intuitionistic Fuzzy Sets, Volume 24 (2018), Number 1, pages 110–119
|
| DOI:
|
https://doi.org/10.7546/nifs.2018.24.1.110-119
|
| Download:
|
 PDF (203 Kb Kb, File info)
|
| Abstract:
|
InterCriteria Analysis (ICrA) results based on different number of objects are investigated in this paper. To evaluate the influence of the number of objects, data from parameter identification procedures of an E. coli fed-batch fermentation process model are used. Model parameters are estimated applying 100 genetic algorithms with different mutation rate values. Seven different index matrices are constructed for ICrA. The results show that the number of objects in ICrA is important for the reliability of the obtained results.
|
| Keywords:
|
InterCriteria Analysis, Intuitionistic fuzzy sets, Genetic algorithms, Mutation rate, E. coli.
|
| AMS Classification:
|
03E72
|
| References:
|
- Angelova, M., Roeva, O., & Pencheva, T. (2015) InterCriteria Analysis of a Cultivation Process Model Based on the Genetic Algorithm Population Size Influence. Notes on Intuitionistic Fuzzy Sets, 21(4), 90–103.
- Atanassov, K. (2012) On Intuitionistic Fuzzy Sets Theory, Springer, Berlin.
- Atanassov, K. (2010) On Index Matrices, Part 1: Standard Cases. Advanced Studies in Contemporary Mathematics, 20(2), 291–302.
- Atanassov, K., Mavrov, D., & Atanassova, V. (2014) Intercriteria Decision Making: A New Approach for Multicriteria Decision Making, Based on Index Matrices and Intuitionistic Fuzzy Sets. Issues in IFSs and GNs, 11, 1–8.
- Atanassov, K., Atanassova, V., & Gluhchev, G. (2015) InterCriteria Analysis: Ideas and problems. Notes on Intuitionistic Fuzzy Sets, 21(1), 81–88.
- Bastin, G., & Dochain, D. (1991) On-line Estimation and Adaptive Control of Bioreactors, Elsevier Scientific Publications.
- Capko, D., Erdeljan, A., Vukmirovic, S., & Lendak, I. (2011) A hybrid genetic algorithms for partitioning of data model in distribution management system. Information Technology and Control, 40(4), 316–321.
- Goldberg, D. E. (2006) Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley Longman, London.
- Laboudi, Z., & Chikhi, S. (2012) Comparison of genetic algorithms and quantum genetic algorithms. Int. Arab J Inf. Tech., 9(3), 243–249.
- Pencheva, T., Angelova, M., Atanassova, V., & Roeva, O. (2015) InterCriteria analysis of genetic algorithm parameters in parameter identification. Notes on Intuitionistic Fuzzy Sets, 21(2), 99–110.
- Pencheva, T., Roeva, O., & Hristozov, I. (2006) Functional State Approach to Fermentation Processes Modelling, Prof. Marin Drinov Academic Publishing House, Sofia.
- Prasad, G., Singh, D., Mishra, A., & Shah, V. H. (2017) Genetic Algorithm Performance Assessment by Varying Population Size and Mutation Rate in Case of String Reconstruction. Journal of Basic and Applied Engineering Research, 4(2), 157–161.
- Roeva, O., Pencheva, T., Hitzmann, B., & Tzonkov, S. (2004) A Genetic Algorithms Based Approach for Identification of Escherichia coli Fed-batch Fermentation. International Journal Bioautomation, 1, 30–41.
- Roeva, O., & Vassilev, P. (2016) InterCriteria Analysis of Generation Gap Influence on Genetic Algorithms Performance. Advances in Intelligent Systems and Computing, 401, 301–313.
- Roeva, O., Vassilev, P., Fidanova, S., & Paprzycki, M. (2016) InterCriteria Analysis of Genetic Algorithms Performance, Studies of Computational Intelligence, 655, 235–260.
|
| Citations:
|
The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.
|
|
