이산정보의 증가에 따른 아카이케정보척도 기반 신뢰성해석의 정확도 평가Evaluation of Accuracy of Reliability for Increasing Number of Discrete Information using Akaike Information Criterion based Reliability Analysis
- Other Titles
- Evaluation of Accuracy of Reliability for Increasing Number of Discrete Information using Akaike Information Criterion based Reliability Analysis
- Authors
- 임우철; 박상현; 최성식; 이태희
- Issue Date
- Nov-2012
- Publisher
- 대한기계학회
- Keywords
- Reliability Analysis(신뢰성해석); Discrete Information(이산정보); Maximum Likelihood Estimation(MLE: 최우량추정법); Akaike Information Criterion(AIC: 아카이케정보척도); Monte Carlo Simulation(MCS: 몬테카를로 시뮬레이션)
- Citation
- 대한기계학회 2012년도 추계학술대회 논문집, pp.2201 - 2206
- Indexed
- OTHER
- Journal Title
- 대한기계학회 2012년도 추계학술대회 논문집
- Start Page
- 2201
- End Page
- 2206
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/164214
- Abstract
- It is highly inappropriate to perform the reliability analysis for discrete information using earlier developed methods because most of these methods assumed that the distribution of variables is continuous. On the other hand reliability analysis using Akaike information criterion (AIC) is an appropriate method to calculate reliability for discrete information, since it uses discrete information directly which stands as an advantage in reliability analysis. As we know reliability becomes more accurate with increase in number of discrete information. Therefore in this paper, we suggest a suitable number of samples to calculate reliability. To evaluate accuracy of reliability, we compare AIC with Monte Carlo simulation (MCS) using mathematical examples.
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