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Application of Fuzzy Math Simulation to Quantitative Risk Assessment in Pork Production  

Im, Myung-Nam (Department of Food Science and Technology, Dongguk University)
Lee, Seung-Ju (Department of Food Science and Technology, Dongguk University)
Publication Information
Korean Journal of Food Science and Technology / v.38, no.4, 2006 , pp. 589-593 More about this Journal
Abstract
The objective of this study was to evaluate the use of fuzzy math strategy to calculate variability and uncertainty in quantitative risk assessment. We compared the propagation of uncertainty using fuzzy math simulation with Monte Carlo simulation. The risk far Listeria monocytogenes contamination was estimated for carcass and processed pork by fuzzy math and Monte Carlo simulations, respectively. The data used in these simulations were taken from a recent report on pork production. In carcass, the mean values for the risk from fuzzy math and Monte Carlo simulations were -4.393 log $CFU/cm^2$ and -4.589 log $CFU/cm^2$, respectively; in processed pork, they were -4.185 log $CFU/cm^2$ and -4.466 log $CFU/cm^2$ respectively. The distribution of values obtained using the fuzzy math simulation included all of the results obtained using the Monte Carlo simulation. Consequently, fuzzy math simulation was found to be a good alternative to Monte Carlo simulation in quantitative risk assessment of pork production.
Keywords
quantitative risk assessment; fuzzy math simulation; Monte Carlo simulation; pork production;
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Times Cited By KSCI : 1  (Citation Analysis)
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