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Identifying Upper and Lower Possibility Distributions with Rough Set Concept

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New Frontiers in Artificial Intelligence (JSAI 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2253))

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Abstract

In this paper, from upper and lower directions the upper and lower possibility distributions are identified to approximate the given possibility grades, which is regarded as the expert’s knowledge. The upper possibility distribution reflects the optimistic viewpoint of the expert and the lower possibility distribution reflects pessimistic one. The similarities between dual possibility distributions and upper and lower approximations in rough sets theory are investigated. It is obvious that they have homogenous structures.

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References

  1. Z. Pawlak, Rough Sets (Kluwer Academic Publishers, Netherlands, 1991).

    MATH  Google Scholar 

  2. Z. Pawlak and R. Slowinski, Rough set approach to multi-attribute decision analysis,European Journal of Operational Research 72 (1994) 443–459.

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  3. H. Tanaka and P. Guo, Possibilistic Data Analysis for Operations Research (Heidelberg; New York; Physica-Verlag, Feb., 1999).

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  4. H. Tanaka and P. Guo, Portfolio selection based on upper and lower exponential possibility distributions, European Journal of Operational Research 114 (1999) 115–126

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Author information

Authors and Affiliations

  1. Faculty of Economics, Kagawa University, 760-8523, Takamatsu, Kagawa, Japan

    P. Guo

  2. Toyohashi Sozo College, 20-1 Matsushita, 440-8511, Ushikawacho, Toyohashi

    Hideo Tanaka

Authors
  1. P. Guo
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  2. Hideo Tanaka
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Editor information

Editors and Affiliations

  1. Graduate School of Business Science, The University of Tsukuba, Tokyo

    Takao Terano  & Yukio Ohsawa  & 

  2. School of Engineering, The University of Tokyo, Tokyo

    Toyoaki Nishida

  3. Dept.of Computer Science, National Defense Academy, Japan

    Akira Namatame

  4. School of Medicines, Shimane Medical University, Japan

    Syusaku Tsumoto

  5. The Institute of Scientific and Industrial Research, Osaka University, Osaka

    Takashi Washio

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© 2001 Springer-Verlag Berlin Heidelberg

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Guo, P., Tanaka, H. (2001). Identifying Upper and Lower Possibility Distributions with Rough Set Concept. In: Terano, T., Ohsawa, Y., Nishida, T., Namatame, A., Tsumoto, S., Washio, T. (eds) New Frontiers in Artificial Intelligence. JSAI 2001. Lecture Notes in Computer Science(), vol 2253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45548-5_30

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  • DOI: https://doi.org/10.1007/3-540-45548-5_30

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43070-4

  • Online ISBN: 978-3-540-45548-6

  • eBook Packages: Springer Book Archive

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