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Multiobjective Evolutionary Algorithm for Classifying Cosmic Particles

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Artificial Intelligence and Soft Computing (ICAISC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12854))

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Abstract

Classification is the process of predicting the class of objects. It is a type of Supervised Machine Learning, where predefined labels are assigned to objects, based on predetermined criteria. The article presents the idea of the Multiobjective Evolutionary Algorithm (MEA) that supports solving this problem. The proposed MEA uses two optimization criteria: the number of correctly assigned objects and the total distance between objects within the classes. In the process of multiobjective optimization, the algorithm minimizes the number of incorrectly assigned objects and maximizes the consistency of members within classes. The algorithm was tested on a few benchmarks and used to classify cosmic particles, based on their traces detected in Water Cherenkov Detectors (WCD). The results of the experiments suggest that the proposed algorithm takes advantage of the standard single-objective evolutionary algorithm in solving this problem. The algorithm can be also used for solving similar optimization problems.

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Authors and Affiliations

  1. Faculty of Physics and Applied Informatics, University of Lodz, Lodz, Poland

    Krzysztof Pytel

Authors
  1. Krzysztof Pytel
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Correspondence to Krzysztof Pytel .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Pytel, K. (2021). Multiobjective Evolutionary Algorithm for Classifying Cosmic Particles. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2021. Lecture Notes in Computer Science(), vol 12854. Springer, Cham. https://doi.org/10.1007/978-3-030-87986-0_38

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  • DOI: https://doi.org/10.1007/978-3-030-87986-0_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87985-3

  • Online ISBN: 978-3-030-87986-0

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