Гл. ас. д-р Мария Ангелова | Публикации

Начало | Публикации

Списък на публикациите

  1. Pencheva T., M. Angelova, Intuitionistic Fuzzy Logic Implementation to Assess Purposeful Model Parameters Genesis, Chapter 11 in: Sgurev V., R. Yager, J. Kacprzyk, K. Atanassov (Eds.), Recent Contributions on Intelligent Systems, Studies Computational Intelligence, Vol. 657, 2017, ISBN 978-3-319-41437-9, in press.
  2. Pencheva T., M. Angelova, Modified Multi-Population Genetic Algorithms for Parameter Identification of Yeast Fed-Batch Cultivation, Bulgarian Chemical Communications, 2016, in press.
  3. Roeva O., T. Pencheva, M. Angelova, P. Vassilev, InterCriteria Analysis by Pairs and Triples of Genetic Algorithms Application for Models Identification, Fidanova S. (Ed.) Recent Advances in Computational Optimization, Studies in Computational Intelligence 655, DOI 10.1007/978-3-319-40132-4_12, Springer, 2016, in press.
  4. Pencheva T., M. Angelova, P. Vassilev, O. Roeva, InterCriteria Analysis Approach to Parameter Identification of a Fermentation Process Model, In: Atanassov K. T., O. Castillo, J. Kacprzyk, M. Krawczak, P. Melin, S. Sotirov, E. Sotirova, E. Szmidt, G. De Tré, S. Zadrożny (Eds), Novel Developments in Uncertainty Representation and Processing, Vol. 401 of Advances in Intelligent Systems and Computing, 2016, 385-397, ISBN 978-3-319-26210-9, ISBN 978-3-319-26211-6 (eBook), SJR (2015) = 0.153.
  5. Pencheva T., M. Angelova, K. Atanassov, Genetic Algorithms Quality Assessment Implementing Intuitionistic Fuzzy Logic, Chapter 49 in: Research Methods: Concepts, Methodologies, Tools, and Applications (4 Volumes), IGI Global, Hershey, Pennsylvania (USA), 2015, Vol. 3-4, 1125-1152, DOI 10.4018/978-1-4666-7456-1.ch049, ISBN13 9781466674561, ISBN10 1466674563, EISBN13 9781466674578.
  6. Angelova M., O. Roeva, T. Pencheva, InterCriteria Analysis of a Cultivation Process Model Based on the Genetic Algorithm Population Size Influence, Notes on Intuitionistic Fuzzy Sets, 2015, 21(4), 90-103, ISSN 1310-4926.
  7. Roeva O., P. Vassilev, M. Angelova, T. Pencheva, InterCriteria Analysis of Parameters Relations in Fermentation Processes Models, Chapter in: Computational Collective Intelligence, Lecture Notes in Computer Science, 2015, 9330, 171-181, ISBN 978-3-319-24305-4, ISBN 978-3-319-23406-1 (eBook), SJR 0.252.
  8. Angelova M., O. Roeva, T. Pencheva, InterCriteria Analysis of Crossover and Mutation Rates Relations in Simple Genetic Algorithm, Annals of Computer Science and Information Systems, 2015, 5, 419-424, ISSN 2300-5963, ISBN 978-83-60810-66-8.
  9. Pencheva T., M. Angelova, V. Atanassova, O. Roeva, InterCriteria Analysis of Genetic Algorithm Parameters in Parameter Identification, Notes on Intuitionistic Fuzzy Sets, 2015, 21(2), 99-110, ISSN 1310-4926.
  10. Pencheva T., M. Angelova, Purposeful Model Parameters Genesis in Multi-population Genetic Algorithm, Global Journal of Technology and Optimization, 2014, 5:164, DOI 10.4172/1410-3217.1000164, ISSN 2229-8711.
  11. Angelova M., T. Pencheva, Genetic Operators Significance Assessment in Simple Genetic Algorithm, Lecture Notes in Computer Science, 2014, 8353, 223-231, ISBN 978-3-662-43879-4, SJR 0.305.
  12. Angelova M., T. Pencheva, Genetic Operators’ Significance Assessment in Multi-population Genetic Algorithms, International Journal of Metaheuristics, 2014, 3(2), 162-173, ISSN 1755-2176, E-ISSN 1755-2184.
  13. Angelova M., Modified Genetic Algorithms and Intuitionistic Fuzzy Logic for Parameter Identification of a Fed-batch Cultivation Model, PhD Thesis, Sofia (2014), (in Bulgarian)
  14. Pencheva T., M. Angelova, K. Atanassov, Quality Assessment of Multi-population Genetic Algorithms Performance, International Journal of Scientific and Engineering Research, 2013, 4(12), 1870-1875.
  15. Angelova M., K. Atanassov, T. Pencheva, Intuitionistic Fuzzy Logic as a Tool for Quality Assessment of Genetic Algorithms Performances, Fidanova S. (Ed.), Recent Advances in Computational Optimization, SCI 470 (Studies in Computational Intelligence, Vol. 470), Springer, 2013, 1-13, ISBN 978-3-319-00409-9, SJR 0.211.
  16. Pencheva T., M. Angelova, K. Atanassov, Genetic Algorithms Quality Assessment Implementing Intuitionistic Fuzzy Logic, Chapter 11 in: Vasant P. (Ed.), Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications, IGI Global, Hershey, Pennsylvania (USA), 2013, 327-354. DOI 10.4018/978-1-4666-4450-2, ISBN13 9781466644502, ISBN10 1466644508, EISBN13 9781466644519.
  17. Angelova M., T. Pencheva, Improvement of Multi-population Genetic Algorithm Convergence Time, Chapter 1 in: Monte Carlo Methods and Applications, (Eds. Sabelfeld K. K., I. Dimov), 2013, 1-9, De Gruyter, Berlin, Germany, ISBN 9783110293586 (eBook).
  18. Angelova M., K. Atanassov, T. Pencheva, Intuitionistic Fuzzy Logic based Quality Assessment of Simple Genetic Algorithm, Vol. 2: Proceedings of the 16th International Conference on System Theory, Control and Computing (ICSTCC), October 12-14, 2012, Sinaia, Romania, ISBN 978-606-8348-48-3, Electronic edition.
  19. Angelova M., K. Atanassov, T. Pencheva, Multi-population Genetic Algorithm Quality Assessment Implementing Intuitionistic Fuzzy Logic, Proceedings of the Federated Conference on Computer Sciences and Information Systems (Workshop on Computational Optimization – WCO’2012), Wrocław, Poland, September 9-12, 2012, 365-370, ISBN 978-83-60810-51-4.
  20. Angelova M., K. Atanassov, T. Pencheva, Intuitionistic Fuzzy Estimations of Purposeful Model Parameters Genesis, 2012 IEEE 6th International Conference “Intelligent Systems”, Sofia, Bulgaria, September 6-8, 2012, 206-211, ISBN 978-1-4673-2277-5.
  21. Angelova M., P. Melo-Pinto, T. Pencheva, Modified Simple Genetic Algorithms Improving Convergence Time for the Purposes of Fermentation Process Parameter Identification, WSEAS Transactions on Systems, 2012, 11(7), 256-267, E-ISSN 2224-2678, SJR 0.319.
  22. Ангелова М., Т. Пенчева, Целенасочен параметричен генезис с многопопулационен генетичен алгоритъм, X Национална младежка научно-практическа сесия, 23-25 Април 2012, София, 250-254, ISBN 1314-0698.
  23. Ангелова М., Т. Пенчева, Процедура за сравнение качеството на генетични алгоритми чрез приложение на интуиционистки размита логика, X Национална младежка научно-практическа сесия, 23-25 Април 2012, София, 244-249, ISBN 1314-0698.
  24. Angelova M., K. Atanassov, T. Pencheva, Purposeful Model Parameters Genesis in Simple Genetic Algorithms, Computers & Mathematics with Applications, 2012, 64, 221-228, ISSN 0898-1221, IF 1.747.
  25. Angelova M., T. Pencheva, Algorithms Improving Convergence Time in Parameter Identification of Fed-batch Cultivation, Comptes rendus de l’Académie bulgare des Sciences, 2012, 65(3), 299-306, ISSN 1310-1331, IF 0.28.
  26. Angelova M., T. Pencheva, Sensitivity Analysis for the Purposes of Parameter Identification of a S. cerevisiae Fed-batch Cultivation, Lecture Notes in Computer Science, 2012, 7116, 165-172, ISBN 978-3-642-29842-4, SJR 0.308.
  27. Angelova M., T. Pencheva, Tuning Genetic Algorithm Parameters to Improve Convergence Time, International Journal of Chemical Engineering, 2011, Article ID 646917, DOI 10.1155/2011/646917, http://www.hindawi.com/journals/ijce/2011/646917/cta/, SJR 0.204.
  28. Angelova M., St. Tzonkov, T. Pencheva, Genetic Algorithms based Parameter Identification of Yeast Fed-batch Cultivation, Lecture Notes in Computer Science, 2011, 6046, 224-231, ISBN 978-3-642-18465-9 (Print), 978-3-642-18466-6 (Online), SJR 0.308.
  29. Ангелова М., Т. Пенчева, Изследване влиянието на последователността на изпълнение на операторите на генетичните алгоритми за параметрична идентификация на ферментационен процес, Сборник доклади от 8-ма Национална младежка научно-практическа сесия, София, 10-11 Май 2010, 50-55, ISSN 1314-0698.
  30. Ilkova T., M. Petrov, M. Angelova, Optimal Feed Rate Strategy of Biotechnological Process in L-lysine Production Using Neuro-Dynamic Control, Information Technologies and Control, 2010, Year VIII, 4, 32-39
  31. Angelova M., S. Tzonkov, T. Pencheva, Parameter Identification of a Fed-batch Cultivation of S. cerevisiae using Genetic Algorithms, Serdica Journal of Computing, 2010, 4(1), 11-18, ISSN 1312-6555.
  32. Angelova M., St. Tzonkov, T. Pencheva, Modified Multi-population Genetic Algorithm for Yeast Fed-batch Cultivation Parameter Identification, Int J Bioautomation, 2009, 13(4), 163-172, ISSN 1313-261X.