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Computational Intelligence for Risk and Disaster Management

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3 Author(s)
Engemann, K.J. ; Iona Coll., New Rochelle ; Miller, H.E. ; Yager, R.R.

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.

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Fuzzy Systems, 2006 IEEE International Conference on

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