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Using Ant Colony Optimization and Genetic Algorithms for the Linguistic Summarization of Creep Data

  • Conference paper
Intelligent Systems'2014

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 322))

Abstract

Some models using metaheuristics based in an “improvement of solutions” procedure, specifically Genetic Algorithms (GA), have been proposed previously to the linguistic summarization of numerical data (LDS). In the present work is proposed a new model for LDS based in Ant Colony Optimization (ACO), a metaheuristic that use a “construction of solution” procedure. Both models are compared in LDS over creep data. Results show how the ACO based model overcomes the measures of goodness of the final summary but fails to improve the results of the GA based model in relation to the diversity of the summary. Features of both models are considered to explain the results.

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Author information

Authors and Affiliations

  1. Informatic Studies Center, Universidad Central Marta Abreu de Las Villas, Santa Clara, Cuba

    Carlos A. Donis-Díaz & Rafael Bello

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

Authors
  1. Carlos A. Donis-Díaz
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  2. Rafael Bello
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  3. Janusz Kacprzyk
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Corresponding author

Correspondence to Carlos A. Donis-Díaz .

Editor information

Editors and Affiliations

  1. School of Computing and Communications, Lancaster University, Lancaster, United Kingdom

    P. Angelov

  2. Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    K.T. Atanassov

  3. Intelligent Systems Department, Bulgarian Academy of Sciences Inst. of Infor. & Communication Techn., Sofia, Bulgaria

    L. Doukovska

  4. Metalurgy, University of Chemical Technology and, Sofia, Bulgaria

    M. Hadjiski

  5. University of Library Studies and IT (ULSIT), Sofia, Bulgaria

    V. Jotsov

  6. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    J. Kacprzyk

  7. Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand

    N. Kasabov

  8. Intelligent Systems Laboratory, Prof. Assen Zlatarov University Faculty of Technical Sciences, Bourgas, Bulgaria

    S. Sotirov

  9. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    E. Szmidt

  10. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    S. Zadrożny

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Donis-Díaz, C.A., Bello, R., Kacprzyk, J. (2015). Using Ant Colony Optimization and Genetic Algorithms for the Linguistic Summarization of Creep Data. In: Angelov, P., et al. Intelligent Systems'2014. Advances in Intelligent Systems and Computing, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-11313-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-11313-5_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11312-8

  • Online ISBN: 978-3-319-11313-5

  • eBook Packages: EngineeringEngineering (R0)

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