Re: A question on fuzzy multiple attributes decision-making


Subject: Re: A question on fuzzy multiple attributes decision-making
From: Aureli Soria Frisch (Aureli.Soria_Frisch@ipk.fhg.de)
Date: Mon Jul 31 2000 - 18:11:11 MET DST


At 22:00 Uhr +0200 30.07.2000, Keping Chen wrote:
>Dear List,
>
>I currently involve in a risk analysis project using fuzzy-based
>Multi-Criteria Evaluation (MCE). The project is to compare the composite
>risk levels across a series of locations. Four input factors, namely
>tropical cyclone, earthquake, hail and tornado, are considered. Given that
>individual scales (e.g. low, medium, high) for the above each factor are
>known, I use a simple stanardisation approach to converting these
>linguistic terms to fuzzy numbers to crisp numbers ranging 0 to 1.
>Individual weights, which reflect the relative importance between
>factors, are also estimated. Finally I calculate a composite value for
>each location with the weighted linear combination method.

Fuzzy integral is a non-linear aggregation operator used, among others, in
decision making. In this framework you can assign weights to individual
factors and to their combination (made in form so called fuzzy measures).
Further it overcomes the "simple" weighted combination of factors.

I am sure you will find the topic very interesting. You can find detailed
information in:

M. Grabisch et. al. (1995), Fundamentals of Uncertainty Calculi with
Applications to Fuzzy Inference, Kluwer Academic Publishers.

Maybe you find there answers to your concrete questions... I hope so,

Regards,
Aureli Soria-Frisch

**************************************
Aureli Soria-Frisch
Fraunhofer IPK, Dept. Pattern Recognition
Pascalstr. 8-9, 10587 Berlin, Germany
e-mail:aureli.soria_frisch@ipk.fhg.de
**************************************

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