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Nature Inspired Clustering – Use Cases of Krill Herd Algorithm and Flower Pollination Algorithm

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Interactions Between Computational Intelligence and Mathematics Part 2

Part of the book series: Studies in Computational Intelligence ((SCI,volume 794))

Abstract

Nature inspired metaheuristics were found to be applicable in deriving best solutions for several optimization tasks, and clustering represents a typical problem which can be successfully tackled with these methods. This paper investigates certain techniques of cluster analysis based on two recent heuristic algorithms mimicking natural processes: the Krill Herd Algorithm (KHA) and the Flower Pollination Algorithm (FPA). Beyond presenting both procedures and their implementation for clustering, a comparison with regard to quality of result was performed for fifteen data sets mainly drawn from the UCI Machine Learning Repository. As a validation of the clustering solution, the Calinski-Harabasz Index was also applied. Moreover, the performance of the investigated algorithms was assessed via Rand index value, with classic k-means procedure being employed as a point of reference. In conclusion it was established, KHA and FPA can be considered as being effective clustering tools.

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Authors and Affiliations

  1. Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059, Kraków, Poland

    Piotr A. Kowalski, Szymon Łukasik, Małgorzata Charytanowicz & Piotr Kulczycki

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Piotr A. Kowalski, Szymon Łukasik, Małgorzata Charytanowicz & Piotr Kulczycki

  3. Institute of Mathematics and Computer Science, The John Paul II Catholic University of Lublin, Konstantynów 1 H, 20-708, Lublin, Poland

    Małgorzata Charytanowicz

Authors
  1. Piotr A. Kowalski
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  2. Szymon Łukasik
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  3. Małgorzata Charytanowicz
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  4. Piotr Kulczycki
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Corresponding author

Correspondence to Piotr A. Kowalski .

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Editors and Affiliations

  1. Department of Information Technology, Széchenyi István University, Győr, Hungary

    László T. Kóczy

  2. Department of Mathematics, Faculty of Science, University of Cádiz, Cádiz, Spain

    Jesús Medina-Moreno

  3. Department of Mathematics, Faculty of Economic and Business Sciences, University of Cádiz, Cádiz, Spain

    Eloísa Ramírez-Poussa

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Kowalski, P.A., Łukasik, S., Charytanowicz, M., Kulczycki, P. (2019). Nature Inspired Clustering – Use Cases of Krill Herd Algorithm and Flower Pollination Algorithm. In: Kóczy, L., Medina-Moreno, J., Ramírez-Poussa, E. (eds) Interactions Between Computational Intelligence and Mathematics Part 2. Studies in Computational Intelligence, vol 794. Springer, Cham. https://doi.org/10.1007/978-3-030-01632-6_6

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