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Intelligent Decision Technologies pp 103–112Cite as

Building Multi-Attribute Decision Model Based on Kansei Information in Environment with Hybrid Uncertainty

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 10))

Abstract

The objective of this paper is to build multi attribute decision model considering Kansei information in hybrid uncertain environment. First, fuzzy random variable is explained to deal with the models in hybrid uncertain environment. Second, using fuzzy random variables, linear regression model (FRRM) is formulated. Third, multi-attribute decision model (MADM) is built based on linear regression model. Finally, multi-attribute decision model is presented in presence of Kansei information given by experts in an environment with hybrid uncertainty involving both randomness and fuzziness.

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Author information

Authors and Affiliations

  1. Graduate School of Informtion, Production and System, Waseda University, 2-7 Hibikino, Wakamatsu, Kitakyushu, 808-0135, Fukuoka, Japan

    Junzo Watada & Nureize Arbaiy

Authors
  1. Junzo Watada
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  2. Nureize Arbaiy
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Editor information

Editors and Affiliations

  1. Graduate School of Information, Production and Systems (IPS), Waseda University, 2-7 Hibikino Wakamatsuku, 808-0135, Fukuoka, Kitakyushu, Japan

    Junzo Watada

  2. Sellinger School of Business and Management, Loyola University Maryland, 4501 N Charles Street, 21210, Baltimore, MD, USA

    Gloria Phillips-Wren

  3. School of Electrical and Information Engineering, University of South Australia, Mawson Lakes Campus Adelaide, 5095, South Australia, SA, Australia

    Lakhmi C. Jain

  4. KES International, Shoreham-by-seaWest Sussex, PO Box 2115, BN43 9AF, United Kingdom

    Robert J. Howlett

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Watada, J., Arbaiy, N. (2011). Building Multi-Attribute Decision Model Based on Kansei Information in Environment with Hybrid Uncertainty. In: Watada, J., Phillips-Wren, G., Jain, L.C., Howlett, R.J. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22194-1_11

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  • DOI: https://doi.org/10.1007/978-3-642-22194-1_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22193-4

  • Online ISBN: 978-3-642-22194-1

  • eBook Packages: EngineeringEngineering (R0)

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