• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.345-353
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.201-210
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• 2010

In this study, new methodology to estimate the reliability of a water distribution system using HSPDA model is suggested. In general, the reliability of a water distribution system can be determined by estimating either the ratio of the required demand to the available demand or the ratio of the number of nodes with sufficient pressure head to the number of nodes with insufficient pressure head when the abnormal operating condition occurs. To perform this approach, hydraulic analysis under the abnormal operating condition is essential. However, if the Demand-Driven Analysis (DDA) which is dependant on the assumption that the required demand at a demand node is always satisfied regardless of actual nodal pressure head is used to estimate the reliability of a water distribution system, the reliability may be underestimated due to the defect of the DDA. Therefore, it is necessary to apply the Pressure-Driven Analysis (PDA) having a different assumption to the DDA's which is that available nodal demand is proportion to nodal pressure head. However, because previous study used a semi-PDA model and the PDA model which had limited applicability depending on the characteristics of a network, proper estimation of the reliability of a water distribution system was impossible. Thus, in this study, a new methodology is suggested by using HSPDA model which can overcome weak points of existing PDA model and Available Demand Fraction (ADF) index to estimate the reliability. The HSPDA can simulate the hydraulic condition of a water distribution system under abnormal operating condition and based on the hydraulic condition simulated, ADF index at each node is calculated to quantify the reliability of a water distribution system. The suggested model is applied to sample networks and the results are compared with those of existing method to demonstrate its applicability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.4
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• pp.334-340
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• 2015

Engine derating is often considered for reliability benefits because lower power operation reduces its failure probability. To be derated during operation, however, the engine must be initially overdesigned. The engine overdesign is cost effective only if reliability increased from derating is enough to offset the initial increase in the development cost caused from the overdesign. The purpose of this paper is to provide an analytical model to consider a trade-off between the engine overdesign and derating. We use a logistic regression model to explain reliability growth in the number of hot firing tests for a fixed power level. Using the Transcost model with the reliability growth model, we show that 10% overdesign of Titan rocket engine decreases its development cost by about 9% and 23% depending on the reliability requirement. We also point out that such a cost reduction depends on the fuel type a rocket uses.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1181-1190
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• 2010

When an insurer develops an insurance product, it is very critical to determine reasonable premiums, which is directly related to insurer's profits. There are three methods to determine premiums. Frist, the insurer utilizes premiums paid to the similar cases to the current one. Second, the insurer calculates premiums based on policyholder's past records. The last method is to combine the first with the second one. Based on the three methods, there are two major theories determining premiums, Limited Fluctuation Credibility Theory not based on statistical models and Greatest Accuracy Credibility Theory based on statistical models. There are well-known methods derived from Greatest Accuracy Credibility Theory, such as, Buhlmann model and Buhlmann-Straub model. In this paper, we extend the Buhlmann-Straub model to accommodate the fact that variability grows according to the number of data in practice and suggest a new non-parametric method to estimate the premiums. The suggested estimation method is also applied to the data gained from simulation and compared with the existing estimation method.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.17-27
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• 2007

Since early 1990s, several developed countries have applied the Electronic Toll Collection System (ETCS) to toll roads in order to solve traffic congestion and delay problems at toll plazas. For the successful operation of the ETCS, it is important to correctly forecast the ETCS using rate. In this study, it was conceived to develop a sophisticated demand forecasting model of the ETCS for toll roads in Changwon City The Binary Logit and neural network models were tested for the model considering 11 explaining variables. The best results in prediction accuracy and goodness-of-fit were obtained on the neural network model. However, because of the difficulty in predicting the 11 variables and its fitness in wide range, the Binary Logit model which considers three policy variables only is recommended as the model to forecast the ETCS using rate.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.33-42
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• 2007

Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. From the analysis of mission time, the result of this comparative study shows the excellent performance of Burr coverage model rather than exponential coverage and S-shaped model using NTDS data. This analysis of failure data compared with the Kappa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2311-2318
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.355-366
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• 2002

Nonparametric statistical inference for the parameter of logit model were examined. Usually nonparametric approach is milder than parametric approach based on normal theory assumption. We compared the two nonparametric methods for legit model, the bootstrap and random permutation in the sense of coverage probability. Monte Carlo simulation is conducted for small sample cases. Empirical power of hypothesis test and coverage probability for confidence interval estimation were presented for simple and multiple legit model respectively. An example were also introduced.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.585-589
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• 2002

본 연구에서는 소프트웨어의 출시 이후 주기적인 보수(periodic maintenance)를 고려한 출시 시기 결정 방법을 제시하였다. 출시시기 결정방법에 관한 연구는 소프트웨어의 신뢰성 확보, 사용자 편의성 등에 관한 연구와 더불어 중요한 연구 분야로 여겨지는 분야이다. 일반 적으로 소프트웨어는 출시 이후에도 패치(patch), 서비스팩(service pack)등을 통해 지속적인 보수가 이루어지기 때문에, 출시 이후의 보수를 고려하여 출시시기를 결정하는 방법론이 필요하다. 이를 위해, 출시 이후의 보수정책을 반영한 소프트웨어 신뢰성 성장 모형(software reliability growth model)을 도출하였다. 위 모형을 기반으로 하여 비용과 신뢰성에 근거한 소프트웨어 출시 시점을 결정해 보았다. 제시된 모형의 타당성을 검증하기 위해 예제를 통해 기존의 논문에서 제시되었던 결과들과 비교분석을 해 보았다. 본 연구의 결과는 기존 연구에서 고려되지 않았던 보수 정책을 고려함으로써, 보다 현실에 가까운 모형을 제시하였다는 점에서 의의를 찾을 수 있고, 출시 후 보수 시점, 보수 정책 등의 결정에도 기여할 수 있을 것이다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.133-135
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• 2013

장래의 해상교통량에 대한 정확한 예측은 항로설계 및 해상교통의 안전성 평가 측면에서 중요한 요소이다. 본 연구는 신뢰성 있는 해상교통량을 추정하기 위해 시계열 모델의 지수평활법과 ARIMA 모형을 이용하여 모형의 식별 및 진단 방안을 제시하였다. 제시된 방법의 효과를 검증하기 위하여 주요항만인 부산항, 광양항, 인천항, 평택항의 해상교통량을 예측하였다. 그 결과로 부산항은 ARIMA 모형, 광양항은 Winters 승법 모형, 인천항은 단순계절 모형, 평택항은 ARIMA 모형이 더 적합한 모형으로 알 수 있었으며, 각 항만별 계절에 따라 월별 교통량의 차이를 보이는 것으로 분석되었다. 본 연구 결과는 향후 항로 및 항만설계 또는 해상교통 안전성 평가에 보다 신뢰성 있는 추정치를 제공할 수 있을 것으로 보인다.