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Computing in Accelerator Design and Oprn. by W. Busse, et. al.,

By W. Busse, et. al.,

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Sample text

The major advantage of the method is that, in the cases where the classical one computes the same risk value, however these sites have completely different risk when fuzzy method is applied. The proposed approach presents a better sensitivity in ranking the wind site according to their risk index. A fuzzy formalism [12] opens the way for computerization of the process of risk analysis, using a variety of AI techniques. Where, risk is defined, with respect to any probability(p)/loss(l) combination, as: < RISKp,1 >=< POSSIBLEp,1 > n < SIGNIFICANT FINANCIAL IMPACTp,1 > where <> denotes a fuzzy set, and n is the symbol for the set intersection.

In the decision theory, we refer risk to a three-dimensional concept involving the following natures: (Nl) Adverse outcome for individuals; (N2) Uncertainty over the occurrence, timing, site, or magnitude of that adverse outcome; (N3) Complexity to show precisely by a state equation or a probability distribution. Clearly, due to N3, we know that, risk is a complex phenomenon. When the complex nature is ignored, the concept of risk may reduced to be probabilityrisk, which means that we can find a probability distribution, obeying a statistical law, to show the risk phenomenon properly.

40 000 580 29 Note from the above results that a Relationship Strategy is preferred for both Minor and Major Fires given the use of a Hot Site for all levels of optimism of the decision maker. Given these results, we apply the same method to determine the valuation of the Hot Site alternative. Table 9 displays the results and adds the fixed cost of $125,00 for the hot site. Likewise Table 10 displays the results of the same analysis on the Cold Site alternative with the $50,000 fixed cost added.

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