Abstract
This chapter present an analysis of the effects in quality results that brings the different types of membership functions in an interval type-2 fuzzy system used to adapt some parameters of Particle Swarm Optimization (PSO). Benchmark mathematical functions are used to test the methods and a comparison is performed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Engelbrecht A.P.: Fundamentals of Computational Swarm Intelligence. University of Pretoria, South Africa (2005)
Haupt, R., Haupt, S.: Practical Genetic Algorithms, 2nd edn. A Wiley-Interscience publication, New York (2004)
Hongbo, L., Ajith, A.: A fuzzy adaptive turbulent particle swarm optimization. Int. J. Innovative Comput. Appl. 1(1), 39–47 (2007)
Jang, J., Sun, C., Mizutani, E.: Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. Prentice-Hall, Upper Saddle River (1997)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings IEEE International Conference on Neural Networks, IV. Piscataway, NJ: IEEE Service Center, pp. 1942–1948 (1995)
Kennedy, J., Eberhart, R.: Swarm Intelligence. Morgan Kaufmann, San Francisco (2001)
Liang, Q., Mendel, J.: Interval type-2 fuzzy logic systems: theory and design. IEEE Trans. Fuzzy Syst. 8(5), 535–550 (2000)
Marcin, M., Smutnicki, C.: Test functions for optimization needs (2005)
Olivas, F., Castillo, O.: Optimal design of fuzzy classification systems using PSO with dynamic parameter adaptation through fuzzy logic. Elsevier, Expert systems with applications, pp. 3196–3206 (2012)
Olivas, F., Valdez, F., Castillo, O.: Particle swarm optimization with dynamic parameter adaptation using interval type-2 fuzzy logic for benchmark mathematical functions. In: 2013 World Congress on Nature and Biologically Inspired Computing (NaBIC), pp. 36–40 (2013)
Shi, Y., Eberhart, R.: Fuzzy adaptive particle swarm optimization. In: Evolutionary Computation, pp. 101–106 (2001)
Wang, B., Liang, G., ChanLin, W., Yunlong, D.: A new kind of fuzzy particle swarm optimization FUZZY_PSO algorithm. In: 1st International Symposium on Systems and Control in Aerospace and Astronautics. ISSCAA 2006, pp. 309–311 (2006)
Zadeh, L.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
Zadeh, L.: Fuzzy logic. IEEE Comput. 8, 83–92 (1965)
Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning—I. Inform. Sci. 8, 199–249 (1975)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Olivas, F., Valdez, F., Castillo, O. (2014). A Comparative Study of Membership Functions for an Interval Type-2 Fuzzy System used to Dynamic Parameter Adaptation in Particle Swarm Optimization. In: Castillo, O., Melin, P., Pedrycz, W., Kacprzyk, J. (eds) Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Studies in Computational Intelligence, vol 547. Springer, Cham. https://doi.org/10.1007/978-3-319-05170-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-05170-3_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05169-7
Online ISBN: 978-3-319-05170-3
eBook Packages: EngineeringEngineering (R0)