Issue:InterCriteria Analysis of Bat Algorithm with Parameter Adaptation Using Type-1 and Interval Type-2 Fuzzy Systems

From Ifigenia, the wiki for intuitionistic fuzzy sets and generalized nets
(Redirected from Issue:Nifs/22/3/91-105)
Jump to: navigation, search
shortcut
http://ifigenia.org/wiki/issue:nifs/22/3/91-105
Title of paper: InterCriteria Analysis of Bat Algorithm with Parameter Adaptation Using Type-1 and Interval Type-2 Fuzzy Systems
Author(s):
Olympia Roeva
Institute of Biophysics and Biomedical Engineering, BAS, 105 Acad. G. Bonchev Str., 1113 Sofia, Bulgaria
olympiaAt sign.pngbiomed.bas.bg
Jonathan Perez
Tijuana Institute of Technology,, Calzada Tecnologico s/n, Tijuana, Mexico
tecjonathanAt sign.pnggmail.com
Fevrier Valdez
Tijuana Institute of Technology,, Calzada Tecnologico s/n, Tijuana, Mexico
fevrierAt sign.pngtectijuana.mx
Oscar Castillo
Tijuana Institute of Technology,, Calzada Tecnologico s/n, Tijuana, Mexico
ocastilloAt sign.pngtectijuana.mx
Presented at: 20th International Conference on Intuitionistic Fuzzy Sets, 2–3 September 2016, Sofia, Bulgaria
Published in: "Notes on IFS", Volume 22, 2016, Number 3, pages 91—105
Download: Download-icon.png PDF (132  Kb, Info) Download-icon.png
Abstract: In this paper, InterCriteria Analysis (ICrA) is considered for analysis of the results from application of Type-1 and Interval Type-2 fuzzy logic to dynamic adaptation of Bat Algorithm (BA) parameters. BA is applied to different optimization problems – five benchmark functions. The modification of the BA integrating Type-1 and Interval Type-2 fuzzy logic systems was successfully applied. The both fuzzy systems perform well even the increase of the benchmark functions complexity. Obtained results from ICrA show that the fuzzy systems, Type-1 and Interval Type-2, have similar performance in dynamic BA parameter adaptation.
Keywords: InterCriteria Analysis, Type-1 Fuzzy System, Interval Type-2 Fuzzy System, Bat Algorithm.
AMS Classification: 03E72.
References:
  1. 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 Intuitionistic Fuzzy Sets and Generalized Nets, 11, 1–8.
  2. Atanassov, K., Szmidt, E., & Kacprzyk, J. (2013) On intuitionistic fuzzy pairs, Notes on Intuitionistic Fuzzy Sets, 19(3), 1–13.
  3. Atanassov, K. (2010) On index matrices, Part 1: Standard cases, Advanced Studies in Contemporary Mathematics, 20(2), 291–302.
  4. Atanassov, K. (2010) On index matrices, Part 2: Intuitionistic fuzzy case, Proceedings of the Jangjeon Mathematical Society, 13(2), 121–126.
  5. Atanassov, K. (2012) On Intuitionistic Fuzzy Sets Theory, Springer, Berlin.
  6. Atanassov, K., Atanassova, V., & Gluhchev, G. (2015) InterCriteria analysis: Ideas and problems, Notes on Intuitionistic Fuzzy Sets, 21(1), 81–88.
  7. Atanassova, V., Mavrov, D., Doukovska, L., Atanassov, K. (2014) Discussion on the Threshold Values in the InterCriteria Decision Making Approach, Notes on Intuitionistic Fuzzy Sets, 20( 2), 94–99.
  8. Atanassova, V., (2015) Interpretation in the Intuitionistic Fuzzy Triangle of the Results, Obtained by the InterCriteria Analysis, Proc. of 16th World Congress of the International Fuzzy Systems Association (IFSA), 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), 30.06-03.07.2015, Gijon, Spain, 1369–1374.
  9. Atanassova, V., Doukovska, L., Atanassov, K., & Mavrov, D. (2014) Intercriteria Decis-ion Making Approach to EU Member States Competitiveness Analysis, In: Shishkov, B. (Ed.), Proc. of the International Symposium on Business Modeling and Software Design – BMSD’14, 289–294.
  10. Bureva, V., Sotirova, E., Sotirov, S., & Mavrov, D. (2015) Application of the InterCriteria Decision Making Method to Bulgarian Universities Ranking, Notes on Intuitionistic Fuzzy Sets, 21(2), 111–117.
  11. Doukovska, L., & Atanassova, V. (2015) InterCriteria Analysis Approach in Radar Detection Threshold Analysis, Notes on Intuitionistic Fuzzy Sets, 21(4), 129–135.
  12. Gandomi, A., & Yang, X. S. (2014) Chaotic Bat Algorithm, Journal of Computational Science, 5(2), 224–232.
  13. Ilkova, T., & Petrov, M. (2015) Using InterCriteria Analysis for Assessment of the Pollution Indexes of the Struma River, Advances in Intelligent System and Computing, Novel Developments in Uncertainty Representation and Processing, Springer, Vol. 401, 351–364.
  14. Pencheva, T., Angelova, M., Vassilev, P., & Roeva, O. (2016) InterCriteria Analysis Approach to Parameter Identification of a Fermentation Process Model, Advances in Intelligent Systems and Computing, Vol. 401, 385–397.
  15. Perez, J., Valdez, F., Castillo, O., & Roeva, O. (2016) Bat Algorithm with Parameter Adaptation Using Interval Type-2 Fuzzy Logic for Benchmark Mathematical Functions, Proc. of 8th International IEEE Conference on Intelligent Systems, 120–127.
  16. Roeva, O., Fidanova, S. & Paprzycki, M. (2016) InterCriteria Analysis of ACO and GA Hybrid Algorithms, Studies in Computational Intelligence, Vol. 610, 107–126.
  17. Roeva, O., Fidanova, S., Vassilev, P., & Gepner, P. (2015) InterCriteria Analysis of a Model Parameters Identification Using Genetic Algorithm, Annals of Computer Science and Information Systems, 5, 501–506.
  18. Sotirov, S., Atanassova, V., Sotirova, E., Bureva, V., Mavrov, D. (2015) Application of the Intuitionistic Fuzzy InterCriteria Analysis Method to a Neural Network Preprocessing Procedure, Proc. of 16th World Congress of the International Fuzzy Systems Association (IFSA), 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), 30.06-03.07.2015, Gijon, Spain, 1559–1564.
  19. Vassilev, P., Todorova, L. & Andonov, V. (2015) An Auxiliary Technique for InterCriteria Analysis Via a Three Dimensional Index Matrix, Notes on Intuitionistic Fuzzy Sets, 21(2), 71–76.
  20. Wang, G., & Guo, L. (2013) A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization, Journal of Applied Mathematics, Vol. 2013, 21 pages.
  21. Yang, X. S. (2010) A New Metaheuristic Bat-Inspired Algorithm, Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), Studies in Computational Intelligence, Vol. 284, 65–74.
  22. Yang, X. S. (2011) Bat Algorithm for Multiobjective Optimization, International Journal of Bio-inspired Computation, 3(5), 267–274.
  23. Yang, X. S., Fister I., Rauter, S., Ljubic, K., & Fister, I., Jr. (2015) Planning the Sports Training Sessions with the Bat Algorithm, Neurocomputing, 149, 993–1002.
  24. Yilmaz, S., & Küçüksille, E. (2015) A New Modification Approach on Bat Algorithm for Solving Optimization Problems, Applied Soft Computing, 28, 259–275.
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.