Abstract
In this paper a new method for dynamic parameter adaptation in particle swarm optimization (PSO) is proposed. PSO is a metaheuristic inspired in social behaviors, which is very useful in optimization problems. In this paper we propose an improvement to the convergence and diversity of the swarm in PSO using fuzzy logic. Simulation results show that the proposed approach improves the performance of PSO.
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Aeberhard, S., Coomans, D., de Vel O.: Comparison of classifiers in high dimensional settings. Technical Report no. 92-02, (1992), Department of Computer Science and Department of Mathematics and Statistics, James Cook University of North Queensland
Bohanec, M., Rajkovic, V.: Knowledge acquisition and explanation for multi-attribute decision making. In: 8th International Workshop on Expert Systems and their Applications, pp. 59–78. Avignon, France (1988)
Cortez, P., Cerdeira, A., Almeida, F., Matos, T., Reis, J.: Modeling wine preferences by data mining from physicochemical properties. Decis. Support Syst. 47(4), 547–553 (2009)
Engelbrecht, A.: Fundamentals of Computational Swarm Intelligence. University of Pretoria, South Africa
Fisher, R.: The use of multiple measurements in taxonomic problems. Ann. Eugenics 7, 179–188 (1936)
Haupt, R., Haupt, S.: Practical Genetic Algorithms, 2nd edn. A Wiley-Interscience publication, New Jersey (1988)
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)
Jossinet, J.: Variability of impedivity in normal and pathological breast tissue. Med. Biol. Eng. Comput. 34, 346–350 (1996)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, IV, pp. 1942–1948. IEEE Service Center, Piscataway (1995)
Kennedy, J., Eberhart, R.: Swarm Intelligence. Morgan Kaufmann, San Francisco (2001)
Marcin, M., Smutnicki, C.: Test functions for optimization needs. Available at: http://www.bioinformaticslaboratory.nl/twikidata/pub/Education/NBICResearchSchool/Optimization/VanKampen/BackgroundInformation/TestFunctions-Optimization.pdf (2005)
Waugh, S.: Extending and benchmarking cascade-correlation. PhD thesis, Computer Science Department, University of Tasmania (1995)
Wolberg, W., Mangasarian, O.: Multisurface method of pattern separation for medical diagnosis applied to breast cytology. Proc. Nat. Acad. Sci. 87, 9193–9196 (1990)
Zadeh, L.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
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Olivas, F., Valdez, F., Castillo, O. (2015). Fuzzy Classification System Design Using PSO with Dynamic Parameter Adaptation Through Fuzzy Logic. In: Castillo, O., Melin, P. (eds) Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics. Studies in Computational Intelligence, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-10960-2_2
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DOI: https://doi.org/10.1007/978-3-319-10960-2_2
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