Abstract
In this paper a new approach for PSO algorithm driven by chaotic pseudorandom number generator is investigated. The ensemble learning method that has been successfully implemented in many evolutionary computational techniques is applied here for the selection of priority factors in the velocity calculations formula. The goal is to improve the performance of chaos driven PSO. The promising results are compared with previously published results of SPSO-2011 on the CEC´ 13 benchmark set.
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Pluhacek, M., Senkerik, R., Zelinka, I., Davendra, D. (2014). Chaos Driven PSO with Ensemble of Priority Factors. In: Zelinka, I., Suganthan, P., Chen, G., Snasel, V., Abraham, A., Rössler, O. (eds) Nostradamus 2014: Prediction, Modeling and Analysis of Complex Systems. Advances in Intelligent Systems and Computing, vol 289. Springer, Cham. https://doi.org/10.1007/978-3-319-07401-6_9
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DOI: https://doi.org/10.1007/978-3-319-07401-6_9
Publisher Name: Springer, Cham
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