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Recent Study on the Application of Hybrid Rough Set and Soft Set Theories in Decision Analysis Process

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Trends in Applied Knowledge-Based Systems and Data Science (IEA/AIE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9799))

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Abstract

Many approaches and methods have been proposed and applied in decision analysis process. One of the most popular approaches that has always been investigated is parameterization method. This method helps decision makers to simplify a complex data set. The purpose of this study was to highlight the roles and the implementations of hybrid rough set and soft set theories in decision-making especially in parameter reduction process. Rough set and soft set theories are the two powerful mathematical tools that have been successfully proven by many research works as a good parameterization method. Both of the theories have the capability of handling data uncertainties and data complexity problems. Recent studies have also shown that both rough set and soft set theories can be integrated together in solving different problems by producing a variety of algorithms and formulations. However, most of the existing works only did the performance validity test with a small volume of data set. In order to prove the hypothesis, which is the hybridization of rough set and soft set theories could help to produce a good result in the classification process, a new alternative to hybrid parameterization method is proposed as the outcome of this study. The results showed that the proposed method managed to achieve significant performance in solving the classification problem compared to other existing hybrid parameter reduction methods.

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Acknowledgements

The authors would like to thank anonymous reviewers for their constructive comments and valuable suggestions. The authors wish to thank Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-02G31 and Ministry of Higher Education Malaysia (MOHE) under the Fundamental Research Grant Scheme (FRGS Vot-4F551) for completion of the research.

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Authors and Affiliations

  1. UTM-IRDA Digital Media Centre, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia

    Masurah Mohamad

  2. Faculty of Computing, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia

    Ali Selamat

Authors
  1. Masurah Mohamad
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  2. Ali Selamat
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Corresponding author

Correspondence to Ali Selamat .

Editor information

Editors and Affiliations

  1. Iwate Prefectural University , Iwate, Japan

    Hamido Fujita

  2. Department Computer Science, Texas State University, San Marcos, Texas, USA

    Moonis Ali

  3. Universiti Teknologi Malaysis (UTM), Bahru, Malaysia

    Ali Selamat

  4. Iwate Prefectural University , Iwate, Japan

    Jun Sasaki

  5. Iwate Prefectural University , Iwate, Japan

    Masaki Kurematsu

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Mohamad, M., Selamat, A. (2016). Recent Study on the Application of Hybrid Rough Set and Soft Set Theories in Decision Analysis Process. In: Fujita, H., Ali, M., Selamat, A., Sasaki, J., Kurematsu, M. (eds) Trends in Applied Knowledge-Based Systems and Data Science. IEA/AIE 2016. Lecture Notes in Computer Science(), vol 9799. Springer, Cham. https://doi.org/10.1007/978-3-319-42007-3_61

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  • DOI: https://doi.org/10.1007/978-3-319-42007-3_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42006-6

  • Online ISBN: 978-3-319-42007-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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