• Title/Summary/Keyword: fuzzy risk

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

  • Im, Myung-Nam;Lee, Seung-Ju
    • Food Science and Biotechnology
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    • v.16 no.3
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    • pp.361-366
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    • 2007
  • 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.

Trust Measuring of e-Marketplace Buyers and Sellers - Design of Fuzzy-based Methodology - (e-마켓플레이스 판매자와 구매자 신뢰도 측정 - 퍼지기반 방법론 설계 -)

  • Yang, Kun-Woo;Cho, Hyuk-Soo
    • International Commerce and Information Review
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    • v.9 no.1
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    • pp.3-21
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    • 2007
  • The explosive growth of e-marketplace transactions requires an appropriate trust measuring framework to protect involving transacting entities such as buyers and sellers. As a strategic competitive edge, e-marketplace service providers have been adopting various system features that make sure no one transacting entity takes a major risk in online transactions involved. In this paper, an improved trust measuring method using fuzzy theory for an e-marketplace is proposed. The proposed methodology incorporates fuzzy set and calculation concepts to help build trust matrices and models, which are used to measure the level of risk involved in a specific e-marketplace transaction concerned. The proposed framework can be utilized to optimize the transaction costs by recommending a differentiated transaction process according to the risk level involved in each online transaction.

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An Fuzzy-based Risk Reasoning Driving Strategy on VANET

  • Lee, Byung-Kwan;Jeong, Yi-Na;Jeong, Eun-Hee
    • Journal of Internet Computing and Services
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    • v.16 no.6
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    • pp.57-67
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    • 2015
  • This paper proposes an Fuzzy-based Risk Reasoning Driving Strategy on VANET. Its first reasoning phase consists of a WC_risk reasoning that reasons the risk by using limited road factors such as current weather, density, accident, and construction, a DR_risk reasoning that reasons the risk by combining the driving resistance with the weight value suitable for the environment of highways and national roads, a DS_risk reasoning that judges the collision risk by using the travel direction, speed. and distance of vehicles and pedestrians, and a Total_risk reasoning that computes a final risk by using the three above-mentioned reasoning. Its second speed reduction proposal phase decides the reduction ratio according to the result of Total_risk and the reduction ratio by comparing the regulation speed of road to current vehicle's speed. Its third risk notification phase works in case current driving speed exceeds regulation speed or in case the Total_risk is higher than AV(Average Value). The Risk Notification Phase informs rear vehicles or pedestrians around of a risk according to drivers's response. If drivers use a brake according to the proposed speed reduction, the precedent vehicles transfers Risk Notification Messages to rear vehicles. If they don't use a brake, a current driving vehicle transfers a Risk Message to pedestrians. Therefore, this paper not only prevents collision accident beforehand by reasoning the risk happening to pedestrians and vehicles but also decreases the loss of various resources by reducing traffic jam.

A Study on the Cost Risk Analysis Method for Construction Projects (건설 프로젝트의 코스트 리스크 분석방법론에 관한 연구)

  • Lee Dong-Un;Kim Yeong-Su
    • Korean Journal of Construction Engineering and Management
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    • v.4 no.4 s.16
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    • pp.201-211
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    • 2003
  • Considering about construction projects characteristics, there Is an existing uncertainty which causes inaccuracy or invalidity under decision making situation. Therefore, cost risk analysis of numerous construction projects are Inclined to depend on expert's experiences and subjective judgements. In Korean domestic construction works, however, there is no reasonable method or process for applying subjective elements. Only probabilistic analysis using objective calculation are being used now. This research suggests a cost risk analysis method to analyze quantitatively Cost Impact by risk, and it appraises expert's subjective elements for the purpose of enhancing validity of cost estimation. Moreover, a new cost risk analysis method is introduced for providing convenient user interface in practical business.

The Limitations of Risk-based Auditing using Fuzzy Methods

  • Mohammadi, Shaban
    • The Journal of Industrial Distribution & Business
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    • v.6 no.1
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    • pp.37-40
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    • 2015
  • Purpose - Investors, creditors, governments, and others make decisions using reasonable information provided by others. In many cases, the users of this information have goals and objectives conflicting with those of the information's producers, indicating the need for external auditors. Research design, data, and methodology - Competition in auditing has noticeably intensified globally, especially in developed countries. This means that auditors are striving to increase the efficiency of their methods. In recent years, risk-based auditing has become prominent among these efforts. In risk-assessment auditing, the auditor may directly affect the effectiveness and efficiency of the audit. Results - As a central framework, the risk assessment process improves audit quality and effectiveness such that the audit will lead to necessary changes. Previous studies have shown that risk assessment affects the nature, timing, and content of audit procedures. Conclusions - In the planning stage of an audit, audit risk assessment may identify any inappropriate or inefficient distribution of resources or determine whether the results of an audit will be ineffective or incorrect. Thus, assessing audit risk is a critical task.

A Study on SIL Allocation for Signaling Function with Fuzzy Risk Graph (퍼지 리스크 그래프를 적용한 신호 기능 SIL 할당에 관한 연구)

  • Yang, Heekap;Lee, Jongwoo
    • Journal of the Korean Society for Railway
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    • v.19 no.2
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    • pp.145-158
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    • 2016
  • This paper introduces a risk graph which is one method for determining the SIL as a measure of the effectiveness of signaling system. The purpose of this research is to make up for the weakness of the qualitative determination, which has input value ambiguity and a boundary problem in the SIL range. The fuzzy input valuable consists of consequence, exposure, avoidance and demand rate. The fuzzy inference produces forty eight fuzzy rule by adapting the calibrated risk graph in the IEC 61511. The Max-min composition is utilized for the fuzzy inference. The result of the fuzzy inference is the fuzzy value. Therefore, using the de-fuzzification method, the result should be converted to a crisp value that can be utilized for real projects. Ultimately, the safety requirement for hazard is identified by proposing a SIL result with a tolerable hazard rate. For the validation the results of the proposed method, the fuzzy risk graph model is compared with the safety analysis of the signaling system in CENELEC SC 9XA WG A10 report.

A Study of SIL Allocation with a Multi-Phase Fuzzy Risk Graph Model (다단계 퍼지 리스크 그래프 모델을 적용한 SIL 할당에 관한 연구)

  • Yang, Heekap;Lee, Jongwoo
    • Journal of the Korean Society for Railway
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    • v.19 no.2
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    • pp.170-186
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    • 2016
  • This paper introduces a multi-phase fuzzy risk graph model, representing a method for determining for SIL values for railway industry systems. The purpose of this paper is to compensate for the shortcomings of qualitative determination, which are associated with input value ambiguity and the subjectivity problem of expert judgement. The multi-phase fuzzy risk graph model has two phases. The first involves the determination of the conventional risk graph input values of the consequence, exposure, avoidance and demand rates using fuzzy theory. For the first step of fuzzification this paper proposes detailed input parameters. The fuzzy inference and the defuzzification results from the first step will be utilized as input parameters for the second step of the fuzzy model. The second step is to determine the safety integrity level and tolerable hazard rate corresponding to be identified hazard in the railway industry. To validate the results of the proposed the multi-phase fuzzy risk graph, it is compared with the results of a safety analysis of a level crossing system in the CENELEC SC 9XA WG A0 report. This model will be adapted for determining safety requirements at the early concept design stages in the railway business.

Estimating Information Security Risk-Using Fuzzy Number Compromising Quantitative and Qualitative Methods (정보 자산 보안 위험 추정-정량적, 정성적 방법을 절충한 퍼지 숫자의 활용)

  • Pak, Ro-Jin;Lee, Dong-Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.19 no.6
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    • pp.175-184
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    • 2009
  • There have been two methods of estimating computer related security risk such as qualitative and quantitative methods which have distinctive advantages or disadvantages. The former is too narrative and somehow abstract to implement and the latter produces concrete result but needs lots of data, so that it is needed to develop a method overcoming such difficulties. It is advised to mix such two methods in a proper way depending on the conditions of a computer system. In this article, a concept of fuzzy number is employed on the way of mixing the two methods and provide a simple example using fuzzy numbers. Simulation was conducted for an assumed model system and it is demonstrated how to calculated expected and unexpected risk.

A framework of Multi Linear Regression based on Fuzzy Theory and Situation Awareness and its application to Beach Risk Assessment

  • Shin, Gun-Yoon;Hong, Sung-Sam;Kim, Dong-Wook;Hwang, Cheol-Hun;Han, Myung-Mook;Kim, Hwayoung;Kim, Young jae
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.3039-3056
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    • 2020
  • Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based on Fuzzy theory, and define Situation Awareness for each time. Finally, we propose a beach risk assessment and prediction model based on linear regression using the calculated risk result and pre-defined risk factors. We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks.

A Development of Fuzzy Logic-Based Evaluation Model for Traffic Accident Risk Level (퍼지 이론을 이용한 교통사고 위험수준 평가모형)

  • 변완희;최기주
    • Journal of Korean Society of Transportation
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    • v.14 no.2
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    • pp.119-136
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    • 1996
  • The evaluation of risk level or possibility of traffic accidents is a fundamental task in reducing the dangers associated with current transportation system. However, due to the lack of data and basic researches for identifying such factors, evaluations so far have been undertaken by only the experts who can use their judgements well in this regard. Here comes the motivation this thesis to evaluate such risk level more or less in an automatic manner. The purpose of this thesis is to test the fuzzy-logic theory in evaluating the risk level of traffic accidents. In modeling the process of expert's logical inference of risk level determination, only the geometric features have been considered for the simplicity of the modeling. They are the visibility of road surface, horizontal alignment, vertical grade, diverging point, and the location of pedestrain crossing. At the same time, among some inference methods, fuzzy composition inference method has been employed as a back-bone inference mechanism. In calibration, the proposed model used four sites' data. After that, using calibrated model, six sites' risk levels have been identified. The results of the six sites' outcomes were quite similar to those of real world other than some errors caused by the enforcement of the model's output. But it seems that this kind of errors can be overcome in the future if some other factors such as driver characteristics, traffic environment, and traffic control conditions have been considered. Futhermore, the application of site's specific time series data would produce better results.

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