earticle

논문검색

Comparison of Monte Carlo Simulation and Fuzzy Math Computation for Validation of Summation in Quantitative Risk Assessment

원문정보

Im, Myung-Nam, Lee, Seung-Ju

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

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 , 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

목차

Abstract
 Introduction
 Materials and Methods
 Results and Discussion
 References

저자정보

  • Im, Myung-Nam Department of Food Science and Technology, Dongguk University
  • Lee, Seung-Ju Department of Food Science and Technology, Dongguk University

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.