Computational Intelligence for Risk and Disaster Management

In this paper we provide a computational intelligence methodology for risk and disaster management using attitudinal and fuzzy modeling. We provide a paradigm representing the relationship among threats, events, control alternatives and losses. In evaluating a control alternative we look beyond the...

Full description

Saved in:
Bibliographic Details
Main Authors: Engemann, K.J., Miller, H.E., Yager, R.R.
Format: Conference Proceeding
Language:English
Subjects:
Computational intelligence
Costs
Disaster management
Dispersion
Fires
Fuzzy control
Investments
Risk analysis
Risk management
Technology management
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper we provide a computational intelligence methodology for risk and disaster management using attitudinal and fuzzy modeling. We provide a paradigm representing the relationship among threats, events, control alternatives and losses. In evaluating a control alternative we look beyond the traditional expected value as a summary measure of expectation and the traditional variance as a measure of dispersion. We introduce a new measure of dispersion which incorporates the decision maker's attitude. We present a fuzzy model to use this attitudinal variance in conjunction with the attitudinal expected value in order to assess the overall value of control alternatives.
ISSN:1098-7584
DOI:10.1109/FUZZY.2006.1681884