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

돈육 생산공정에서의 정량적 위해 평가에 fuzzy 연산의 적용

  • Im, Myung-Nam (Department of Food Science and Technology, Dongguk University) ;
  • Lee, Seung-Ju (Department of Food Science and Technology, Dongguk University)
  • Published : 2006.08.01

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.

돈육 가공 공정에 대한 QRA에 Monte Carlo simulation이 적용된 바 있는데, 새로운 방법으로 fuzzy 연산을 적용하여 Monte Carlo simulation과 비교 분석하였다. Carcass단계에 대한 오염 예측치인 fuzzy 값과 Monte Carlo simulation 확률분포 값의 기술통계량인 평균값은 각각 -4.393 log $CFU/cm^2$, -4.589 log $CFU/cm^2$ 로 나타났으며, processing 단계에서는 -4.185 log $CFU/cm^2$, -4.466 log $CFU/cm^2$으로 두 가지 접근 방법들이 비슷한 경향을 보였다. Fuzzy 값은 Monte Carlo simulation 확률분포 값을 포함하는 것으로 나타났다. 한편 최근 국내에서는 위해 평가에 대한 연구가 많이 이루어지고 있는데 대부분 데이터 분석은 Monte Carlo simulation에만 의존하고 있고, 다른 접근 방법에 대한 연구는 미진한 실정이다. 따라서 본 연구는 위해 평가를 위한 방법적 도구들을 개발하는데 새로운 접근 방향을 제시하였다 또한 향후 fuzzy 연산법은 데이터가 불충분한 위해 평가의 초기 단계에서 유용하게 사용될 수 있는 방법이 될 것이다.

Keywords

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