Paper Info
Title
Computational Intelligence For Risk And Disaster Management
Abstract
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.
Year
DOI
Venue
2006
10.1109/FUZZY.2006.1681884
2006 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5
Keywords
Field
DocType
disasters,computational intelligence,risk management,disaster management,expected value,fuzzy set theory,decision theory
Statistical dispersion,Computer science,Fuzzy set,Risk analysis (engineering),Risk management,Artificial intelligence,Decision theory,Management science,Computational intelligence,Fuzzy logic,Emergency management,Expected value,Machine learning
Conference
ISSN
Citations 
PageRank 
1098-7584
0
0.34
References 
Authors
4
3
Name
Order
Citations
PageRank
Kurt J. Engemann1705.91
Holmes E. Miller21810.01
Ronald R. Yager398521562.99