Building multi-attribute decision model based on Kansei information in environment with hybrid uncertainty

Junzo Watada; Nureize Arbaiy

doi:10.1007/978-3-642-22194-1_11

Building multi-attribute decision model based on Kansei information in environment with hybrid uncertainty

Junzo Watada^*, Nureize Arbaiy

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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.

Original language	English
Title of host publication	Smart Innovation, Systems and Technologies
Pages	103-112
Number of pages	10
Volume	10 SIST
DOIs	https://doi.org/10.1007/978-3-642-22194-1_11
Publication status	Published - 2011
Event	3rd International Conference on Intelligent Decision Technologies, IDT'2011 - Piraeus Duration: 2011 Jul 20 → 2011 Jul 22

Other

Other	3rd International Conference on Intelligent Decision Technologies, IDT'2011
City	Piraeus
Period	11/7/20 → 11/7/22

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Human-Computer Interaction
Software

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10.1007/978-3-642-22194-1_11

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title = "Building multi-attribute decision model based on Kansei information in environment with hybrid uncertainty",

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.",

author = "Junzo Watada and Nureize Arbaiy",

year = "2011",

doi = "10.1007/978-3-642-22194-1_11",

language = "English",

isbn = "9783642221934",

volume = "10 SIST",

pages = "103--112",

booktitle = "Smart Innovation, Systems and Technologies",

note = "3rd International Conference on Intelligent Decision Technologies, IDT'2011 ; Conference date: 20-07-2011 Through 22-07-2011",

}

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T1 - Building multi-attribute decision model based on Kansei information in environment with hybrid uncertainty

AU - Watada, Junzo

AU - Arbaiy, Nureize

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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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U2 - 10.1007/978-3-642-22194-1_11

DO - 10.1007/978-3-642-22194-1_11

M3 - Conference contribution

AN - SCOPUS:84866315478

SN - 9783642221934

VL - 10 SIST

SP - 103

EP - 112

BT - Smart Innovation, Systems and Technologies

T2 - 3rd International Conference on Intelligent Decision Technologies, IDT'2011

Y2 - 20 July 2011 through 22 July 2011

ER -

Building multi-attribute decision model based on Kansei information in environment with hybrid uncertainty

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