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Comparison of Monte Carlo Simulation and Fuzzy Math Computation for Validation of Summation in Quantitative Risk Assessment
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  • Comparison of Monte Carlo Simulation and Fuzzy Math Computation for Validation of Summation in Quantitative Risk Assessment
  • Comparison of Monte Carlo Simulation and Fuzzy Math Computation for Validation of Summation in Quantitative Risk Assessment
저자명
Im. Myung-Nam,Lee. Seung-Ju
간행물명
Food science and biotechnology
권/호정보
2007년|16권 3호|pp.361-366 (6 pages)
발행정보
한국식품과학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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As the application of quantitative risk assessment (QRA) to food safety becomes widespread, it is now being questioned whether experimental results and simulated results coincide. Therefore, this paper comparatively analyzed experimental data and simulated data of the cross contamination, which needs summation of the simplest calculations in QRA, of chicken by Monte Carlo simulation and fuzzy math computation. In order to verify summation, the following basic operation was performed. For the experiment, thigh, breast, and a mixture of both parts were preserved for 24 hr at $20^{circ}C$, and then the cell number of Salmonella spp. was measured. In order to examine the differences between experimental results and simulated results, we applied the descriptive statistics. The result was that mean value by fuzzy math computation was more similar to the experimental than that by Monte Carlo simulation, whereas other statistical descriptors by Monte Carlo simulation were more similar.