• Title/Summary/Keyword: Risk simulation

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A Risk Analysis Simulation Model for Security Management of IT System (IT시스템 보안관리 위험분석 시뮬레이션 모델)

  • Kim, Kang;Cho, Kyoung-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.2
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    • pp.75-81
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    • 2003
  • The Korea standard model is not fitted to general company in many faces because it is made for the public institution. This report suggests the risk analysis Simulation model of Security Management based on korea standard model , to apply and operate for general companies possibly. This model tries to show many standards, come subjectively in the character of the risk analysis, objectively and generally, and tries to give you the possible countermove, which can be operated and actual , for the countermove analysis and presentation.

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Prediction of Dynamic Line Rating Based on Thermal Risk Probability by Time Series Weather Models (시계열 기상모델을 이용한 열적 위험확률 기반 동적 송전용량의 예측)

  • Kim, Dong-Min;Bae, In-Su;Cho, Jong-Man;Chang, Kyung;Kim, Jin-O
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.7
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    • pp.273-280
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    • 2006
  • This paper suggests the method that forecasts Dynamic Line Rating (DLR). Thermal Overload Risk Probability (TORP) of the next time is forecasted based on the present weather conditions and DLR value by Monte Carlo Simulation (MCS). To model weather elements of transmission line for MCS process, this paper will propose the use of statistical weather models that time series is applied. Also, through the case study, it is confirmed that the forecasted TORP can be utilized as a criterion that decides DLR of next time. In short, proposed method may be used usefully to keep security and reliability of transmission line by forecasting transmission capacity of the next time.

Analysis on Ampacity of Overhead Transmission Lines Being Operated

  • Yan, Zhijie;Wang, Yanling;Liang, Likai
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1358-1371
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    • 2017
  • Dynamic thermal rating (DTR) system is an effective method to improve the capacity of existing overhead line. According to the methodology based on CIGRE (International Council on Large Electric systems) standard, ampacity values under steady-state heating balance can be calculated from ambient environmental conditions. In this study, simulation analysis of relations between parameters and ampacity is described as functional dependence, which can provide an effective basis for the design and research of overhead transmission lines. The simulation of ampacity variation in different rating scales is described in this paper, which are determined from real-time meteorological data and conductor state parameters. To test the performance of DTR in different rating scales, capacity improvement and risk level are presented. And the experimental results show that the capacity of transmission line by using DTR has significant improvement, with low probability of risk. The information of this study has an important reference value to the operation management of power grid.

RISK ANALYSIS FOR INDUSTRIAL PROJECT IN CONSTRUCTION PHASE: A MONTE-CARLO SIMULATION APPROACH

  • Soo-Yong Kim;Luu Truong Van;Han-Ki Ha;Nguyen Quoc Tuan
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.130-139
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    • 2007
  • This paper presents a study on risk analysis in terms of contractor's costs in construction phase in which Crystal ball (software of Decisioneering, UK) has been utilized as a main tool. To realize it, a questionnaire survey has been carried out to identify the dominant factors that strongly influence contractor costs in Vietnam. Based on results of questionnaire investigation, the survey identified three factors which were duration of each construction task, costs of reinforcing steel, and cement. Then a spreadsheet model was created in order to analyze risks. The study also indicates that the cost of reinforcing steel and cement are the cause of risks for contractors. According to the suggested model, contractors may foresee the probability of completion within the approved budget, and the possibility of earning in accordance with owner's payment conditions.

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A Risk Analysis Model Using VERT for R & D Project Management (R & D 프로젝트의 위험분석모형의 연구)

  • 황홍석
    • Journal of the Korean Operations Research and Management Science Society
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    • v.20 no.1
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    • pp.85-99
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    • 1995
  • Increasingly, risk analysis is becoming important ingredients in achieving the successful implementation and application in the area of the project management. The project management system is designed to manage or control the project resources on a given activity within time, cost and performance so called TPPM (Total Productive Project Management). In this research, a risk analysis model misproposed to identify potential problem areas, quantify the risks, and generated the chice of the action that can be taken to reduce the risk. In addition two analysis models are proposed : 1) risk factor model and 2) network simulation model using VERT (Venture Evaluation and Review Technique ). The objective of the remodels is to estimate the schedule, cost performance risks. These proposed quantitative models for project risk analysis are proving its value for the project managers who need to assess the risk of changes in cost, schedule, or performance. The proposed models will be used in the area of project selection, evaluation and the allocation of project resources.

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Comparison Of Interval Estimation For Relative Risk Ratio With Rare Events

  • Kim, Yong Dai;Park, Jin-Kyung
    • Communications for Statistical Applications and Methods
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    • v.11 no.1
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    • pp.181-187
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    • 2004
  • One of objectives in epidemiologic studies is to detect the amount of change caused by a specific risk factor. Risk ratio is one of the most useful measurements in epidemiology. When we perform the inference for this measurement with rare events, the standard approach based on the normal approximation may fail, in particular when there are no disease cases observed. In this paper, we discuss and evaluate several existing methods for constructing a confidence interval of risk ratio through simulation when the disease of interest is a rare event. The results in this paper provide guidance with how to construct interval estimates for risk difference and risk ratio when there are no disease cases observed.

A Study on the Method of the Risk Management in the Housing Project (주택사업의 리스크 원인분석 및 대응방안에 관한 연구)

  • Lee, Jong kyu;Lee, Ju Hyung
    • KIEAE Journal
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    • v.8 no.2
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    • pp.79-86
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    • 2008
  • A housing project is very sensitive the changing environment. Therefor, a housing project is the high risk. Therefor in order to be succeed the project it becomes necessary to effectively manage the risk involved in the process of the housing project. This study analysed the risk factors that involved in the process of the housing project as compared with the precede research. The results of this research are as follows : First, complete feasibility study and verification with conviction in market and environment are required. And, securing organization and specificity for simulation and variation of environment are required in the process by step. And then, complaint and flaw are required in the final stage. The results of this study can be used as the guideline to make the risk management system for the housing project.

FUZZY RISK MEASURES AND ITS APPLICATION TO PORTFOLIO OPTIMIZATION

  • Ma, Xiaoxian;Zhao, Qingzhen;Liu, Fangai
    • Journal of applied mathematics & informatics
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    • v.27 no.3_4
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    • pp.843-856
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    • 2009
  • In possibility framework, we propose two risk measures named Fuzzy Value-at-Risk and Fuzzy Conditional Value-at-Risk, based on Credibility measure. Two portfolio optimization models for fuzzy portfolio selection problems are formulated. Then a chaos genetic algorithm based on fuzzy simulation is designed, and finally computational results show that the two risk measures can play a role in possibility space similar to Value-at-Risk and Conditional Value-at-Risk in probability space.

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Feasibility assessment of longevity swap for the Korean life annuity market

  • Lee, Changsoo;Hong, Jimin;Kim, Seongmin
    • Communications for Statistical Applications and Methods
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    • v.28 no.6
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    • pp.655-671
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    • 2021
  • This study analyzes the premium risk of insurers in Korea, which is expected to experience the fastest population aging in the world. Based on the Lee-Carter model, we generate 10,000 scenarios for the number of future survivors in the group of the 10,000 policyholders of life annuity. According to the result of simulation study, the probability of insurer's loss for both groups of male and female policyholders is very low. This result indicates that the premium risk of insurers is not as great as the insurer's concern. This study also suggests introduction of the longevity swap as an alternative to manage the premium risk for the insurer which sells life annuity products. The longevity swap allows insurers to hedge premium risk and reduce capital burden due to the premium risk inherent in life annuity. This study also shows through examples that the counterparty of swap deal may have excess profit in exchange for taking premium risk.

A new extended alpha power transformed family of distributions: properties, characterizations and an application to a data set in the insurance sciences

  • Ahmad, Zubair;Mahmoudi, Eisa;Hamedani, G.G.
    • Communications for Statistical Applications and Methods
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    • v.28 no.1
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    • pp.1-19
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    • 2021
  • Heavy tailed distributions are useful for modeling actuarial and financial risk management problems. Actuaries often search for finding distributions that provide the best fit to heavy tailed data sets. In the present work, we introduce a new class of heavy tailed distributions of a special sub-model of the proposed family, called a new extended alpha power transformed Weibull distribution, useful for modeling heavy tailed data sets. Mathematical properties along with certain characterizations of the proposed distribution are presented. Maximum likelihood estimates of the model parameters are obtained. A simulation study is provided to evaluate the performance of the maximum likelihood estimators. Actuarial measures such as Value at Risk and Tail Value at Risk are also calculated. Further, a simulation study based on the actuarial measures is done. Finally, an application of the proposed model to a heavy tailed data set is presented. The proposed distribution is compared with some well-known (i) two-parameter models, (ii) three-parameter models and (iii) four-parameter models.