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Issue:Parameter adaptation of the Bat Algorithm, using type-1, interval type-2 fuzzy logic and intuitionistic fuzzy logic: Difference between revisions

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{{issue/data
  | conference      =  International Conference on Intuitionistic Fuzzy Sets Theory and Applications, 20–22 April 2016, Beni Mellal, Morocco
  | conference      =  International Conference on Intuitionistic Fuzzy Sets Theory and Applications, 20–22 April 2016, Beni Mellal, Morocco
  | issue          = [[Notes on Intuitionistic Fuzzy Sets/22/2|"Notes on IFS", Volume 22, 2016, Number 2]], pages 87—98
  | issue          = [[Notes on Intuitionistic Fuzzy Sets/22/2|"Notes on Intuitionistic Fuzzy Sets", Volume 22, 2016, Number 2]], pages 87—98
  | file            = NIFS-22-2-087-098.pdf
  | file            = NIFS-22-2-087-098.pdf
  | format          = PDF
  | format          = PDF
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# Castillo, O. & Melin, P. (2012) A review on the design and optimization of interval Type-2 fuzzy controllers, Appl. Soft Computing, 12(4), 1267–1278.
# Castillo, O. & Melin, P. (2012) A review on the design and optimization of interval Type-2 fuzzy controllers, Appl. Soft Computing, 12(4), 1267–1278.
# Roeva, O. & Michalíková, A. (2013) [[Issue:Generalized net model of intuitionistic fuzzy logic control of genetic algorithm parameters|Generalized net model of intuitionistic fuzzy logic control of genetic algorithm parameters]], Notes on Intuitionistic Fuzzy Sets, 19(2), 71–76.
# Roeva, O. & Michalíková, A. (2013) [[Issue:Generalized net model of intuitionistic fuzzy logic control of genetic algorithm parameters|Generalized net model of intuitionistic fuzzy logic control of genetic algorithm parameters]], Notes on Intuitionistic Fuzzy Sets, 19(2), 71–76.
# Roeva, O. & Michalíková, A. (2014) [[Issue:Intuitionistic fuzzy logic control of metaheuristic algorithms parameters via a Generalized net|Intuitionistic fuzzy logic control of metaheuristic algo¬rithms parameters via a Generalized net]], Notes on Intuitionistic Fuzzy Sets, 20(4), 53–58.
# Roeva, O. & Michalíková, A. (2014) [[Issue:Intuitionistic fuzzy logic control of metaheuristic algorithms' parameters via a generalized net|Intuitionistic fuzzy logic control of metaheuristic algorithms' parameters via a generalized net]], Notes on Intuitionistic Fuzzy Sets, 20(4), 53–58.
# Yilmaz, S. & Küçüksille, E. (2015) A new modification approach on bat algorithm for solving optimization problems, Applied Soft Computing, 28, 259–275.
# Yilmaz, S. & Küçüksille, E. (2015) A new modification approach on bat algorithm for solving optimization problems, Applied Soft Computing, 28, 259–275.
# Yang, X. S. (2010) A New Metaheuristic Bat-Inspired Algorithm, Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK.
# Yang, X. S. (2010) A New Metaheuristic Bat-Inspired Algorithm, Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK.

Latest revision as of 11:11, 29 August 2024

shortcut
http://ifigenia.org/wiki/issue:nifs/22/2/87-98
Title of paper: Parameter adaptation of the Bat Algorithm, using type-1, interval type-2 fuzzy logic and intuitionistic fuzzy logic
Author(s):
Jonathan Pérez
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
tecjonathan@gmail.com
Fevrier Valdez
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
fevrier@tectijuana.mx
Olympia Roeva
Institute of Biophysics and Biomedical Engineering, BAS, Sofia, Bulgaria
olympia@biomed.bas.bg
Oscar Castillo
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
ocastillo@tectijuana.mx
Presented at: International Conference on Intuitionistic Fuzzy Sets Theory and Applications, 20–22 April 2016, Beni Mellal, Morocco
Published in: "Notes on Intuitionistic Fuzzy Sets", Volume 22, 2016, Number 2, pages 87—98
Download:  PDF (127  Kb, File info)
Abstract: We describe in this paper the Bat Algorithm (BA) and a proposed enhancement using fuzzy and intuitionistic fuzzy systems to dynamically adapt BA parameters. BA is a metaheuristic algorithm inspired by the behavor of micro bats, which has been applied to different optimization problems obtaining good results. We propose a new method for dynamic parameter adaptation in the BA using Type-1, interval Type-2 fuzzy logic and intuitionistic fuzzy logic. The goal is improving the performance of the BA.
Keywords: Dynamic parameter adaptation, Bat algorithm, Type-1 fuzzy logic, Type-2 fuzzy logic, Intuitionistic fuzzy logic.
AMS Classification: 03E72.
References:
  1. Olivas, F., Valdez, F. & Castillo, O. (2013) Particle swarm optimization with dynamic parameter adaptation using interval type-2 fuzzy logic for benchmark mathematical functions, 2013 World Congress on Nature and Biologically Inspired Computing (NaBIC), 12-14 Aug 2013, Fargo, ND.
  2. Olivas, F., Valdez, F. & Castillo, O. (2015) Dynamic parameter adaptation in Ant Colony Optimization using a fuzzy system for TSP problems, IFSA-EUSFLAT 2015, Gijón, Asturias, Spain, 765–770.
  3. Wang, G. & Guo, L. (2013) A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization, Journal of Applied Mathematics, Volume 2013, 21 pages.
  4. Perez, J., Valdez, F. & Castillo, O. (2015) Modification of the Bat Algorithm using fuzzy logic for dynamic parameter adaptation, CEC2015 IEEE Congress on Evolutionary Computation, Sendai, Japan, May 26, 2015.
  5. Atanassov, K. (1986) Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20(1), 87–96.
  6. Atanassov, K. (1983) Intuitionistic Fuzzy Sets, VII ITKR Session, Sofia, 20-23 June 1983, Reprinted: Int. J. Bioautomation, 2016, 20(S1), S1–S6.
  7. Atanassov, K. (1999) Intuitionistic Fuzzy Sets: Theory and Applications, Springer, Heidelberg.
  8. Atanassov, K. (2012) On Intuitionistic Fuzzy Sets Theory, Springer Physica-Verlag, Berlin.
  9. Atanassov, K. Vassilev, P., Tsvetkov, R. (2013) Intuitionistic Fuzzy Sets, Measures and Integrals. Academic Publishing House "Prof. Marin Drinov", Sofia.
  10. Atanassov, K. (1988) Review and New Results on Intuitionistic Fuzzy Sets, Mathematical Foundations of Artificial Intelligence Seminar, Sofia, 1988, Preprint IM-MFAIS-1-88. Reprinted: Int. J. Bioautomation, 2016, 20(S1), S7–S16.
  11. L Amador-Angulo, L. & Castillo, O. (2014) Optimization of the Type-1 and Type-2 Fuzzy Controller Design for the Water Tank using the Bee Colony Optimization, Norbert Wiener in the 21st Century, (21CW), 2014 IEEE Conference, Boston, MA, 8 pages.
  12. Amador-Angulo, L. & Castillo, O. (2015) Statistical Analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation of the BCO, IFSA-EUSFLAT’2015, 776–783.
  13. Goel, N., Gupta, D. & Goel, S. (2013) Performance of Firefly and Bat Algorithm for Unconstrained Optimization Problems, International Journal of Advanced Research in Computer Science and Software Engineering, 3(5), 1405–1409.
  14. Castillo, O. & Melin, P. (2012) A review on the design and optimization of interval Type-2 fuzzy controllers, Appl. Soft Computing, 12(4), 1267–1278.
  15. Roeva, O. & Michalíková, A. (2013) Generalized net model of intuitionistic fuzzy logic control of genetic algorithm parameters, Notes on Intuitionistic Fuzzy Sets, 19(2), 71–76.
  16. Roeva, O. & Michalíková, A. (2014) Intuitionistic fuzzy logic control of metaheuristic algorithms' parameters via a generalized net, Notes on Intuitionistic Fuzzy Sets, 20(4), 53–58.
  17. Yilmaz, S. & Küçüksille, E. (2015) A new modification approach on bat algorithm for solving optimization problems, Applied Soft Computing, 28, 259–275.
  18. Yang, X. S. (2010) A New Metaheuristic Bat-Inspired Algorithm, Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK.
  19. 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.
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