A spatial fuzzy compromise programming for management of natural disasters / Slobodan S. Simonvic.

By:

Simonvic, Slobodan S

Material type: Text

TextSeries: ICLR Research Paper Series ; ; 24Publication details: [Toronto, Canada] : Institute for Catastrophic Loss Reduction, 2002.Description: 26 p. : ill. ; 30 cmDDC classification:

363.3493/7/097127 22

Partial contents:

Spatial fuzzy compromise programming technique -- Illustrative results of the SFCP application -- Utility of the research results to insurance industry -- Conclusions.

Review: "In this report a new technique named Spatial Fuzzy Compromise Programming (SFCP) has been developed to enhance our ability to address the issues related to uncertainties in spatial environment. A general fuzzy compromise programming technique, when made spatially distributed, proved to be a powerful and flexible addition to the list of techniques available for decision making where multiple criteria are used to judge multiple alternatives. All uncertain variables (subjective and objective) are modeled by way of fuzzy sets. In the present study, fuzzy measures have been introduced to spatial multi criteria decision-making in the GIS environment in order to account for uncertainties." -- p. 4.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	Australian Emergency Management Library	BOOK	363.34937097127 SIM (Browse shelf(Opens below))	Available		900091109

Cover title.

Includes bibliography (pp. 23-26).

Spatial fuzzy compromise programming technique -- Illustrative results of the SFCP application -- Utility of the research results to insurance industry -- Conclusions.

"In this report a new technique named Spatial Fuzzy Compromise Programming (SFCP) has been developed to enhance our ability to address the issues related to uncertainties in spatial environment. A general fuzzy compromise programming technique, when made spatially distributed, proved to be a powerful and flexible addition to the list of techniques available for decision making where multiple criteria are used to judge multiple alternatives. All uncertain variables (subjective and objective) are modeled by way of fuzzy sets. In the present study, fuzzy measures have been introduced to spatial multi criteria decision-making in the GIS environment in order to account for uncertainties." -- p. 4.

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