• 품질경영학회지
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• 제16권2호
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• pp.56-67
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• 1988

It is wellknown that the left truncated exponential distribution with positivity constraint on the location parameter is appropriate as a lifetime distribution model, In this paper, some Bayes estimators of the parameters and reliability for the left truncated exponential lifetime distribution when an unidentified-failure outlier is included and it is excluded in the exchangeable outlier model are proposed, and the performances of these proposed Bayes estimators are also discussed.

• Journal of applied mathematics & informatics
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• 제6권2호
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• pp.661-668
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• 1999

Reliability estimation using Gibbs sampler considered for modeling mixture exponential reliability problems. Gibbs sampler is developed to compute the features of the posterior distribution. Bayesian estimation of complicated functions requires simpler esti-mation techniques due to the mathematical difficulties involved in the Bayes approach. The Maximum likelihood estimator and the Gibbs estimator of reliability of the system are derived. By simula-tion risk behaviors of derived estimators are compared. model de-termination based on relative error is considered. A numerical study with a simulated data set is provided.

• 한국유기농업학회지
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• 제30권2호
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• pp.231-239
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• 2022

The purpose of this study is to provide meaningful information for various stakeholders' decision-making process through forecasting of domestic beef demand. Three different exponential smoothing models were evaluated, and a double exponential smoothing model was used to forecast domestic beef demand based on time-series data, As a result of the forecast, domestic beef consumption is expected to increase by 37,000 to 40,000 tons per year from 2020 to 2025.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.119-132
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• 2006

This paper presents an approach for using right-truncated exponentially distributed random variables to model activity times in stochastic activity networks. The advantages of using the right-truncated exponential distribution are discussed. The moments of a project completion time using the proposed distribution are derived and compared with other estimated moments in literature.

• Journal of Information Science Theory and Practice
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• 제3권3호
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• pp.45-63
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• 2015

The word ‘growth’ represents an increase in actual size, implying a change of state. In science and technology, growth may imply an increase in number of institutions, scientists, or publications, etc. The present study demonstrates the growth of neurology literature for the period 1961-2010. A total of 291,702 records were extracted from the Science Direct Database for fifty years. The Relative Growth Rate (RGR) and Doubling Time (Dt.) of neurology literature have been calculated, supplementing with different growth patterns to check whether neurology literature fits exponential, linear, or logistic models. The results of the study indicate that the growth of literature in neurology does not follow the linear, or logistic growth model. However, it follows closely the exponential growth model. The study concludes that there has been a consistent trend towards increased growth of literature in the field of neurology.

• Communications for Statistical Applications and Methods
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• 제25권4호
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• pp.355-371
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• 2018

The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1391-1396
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• 2008

In this paper, we consider two components system which the lifetimes have Marshall and Olkin's bivariate exponential model with bivariate type I censored data. We propose a Bayesian independent test procedure for above model using fractional Bayes factor method by O'Hagan based on improper prior distributions. And we compute the fractional Bayes factor and the posterior probabilities for the hypotheses, respectively. Also we select a hypothesis which has the largest posterior probability. Finally a numerical example is given to illustrate our Bayesian testing procedure.

• Industrial Engineering and Management Systems
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• 제7권1호
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• pp.44-50
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• 2008

Focusing on the exponential smoothing method equivalent to (1, 1) order ARMA model equation, a new method of estimating smoothing constant using exponential smoothing method is proposed. This study goes beyond the usual method of arbitrarily selecting a smoothing constant. First, an estimation of the ARMA model parameter was made and then, the smoothing constants. The empirical example shows that the theoretical solution satisfies minimum variance of forecasting error. The new method was also applied to the stock market price of electrical machinery industry (6 major companies in Japan) and forecasting was accomplished. Comparing the results of the two methods, the new method appears to be better than the ARIMA model. The result of the new method is apparently good in 4 company data and is nearly the same in 2 company data. The example provided shows that the new method is much simpler to handle than ARIMA model. Therefore, the proposed method would be better in these general cases. The effectiveness of this method should be examined in various cases.

• 한국방재안전학회논문집
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• 제14권2호
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• pp.35-42
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• 2021

본 논문은 전기자동차 충전시설 확충계획에 중요한 요소인 전기자동차 전력 수요량 예측정보를 생산하기 위하여 Exponential Smoothing를 이용하여 전력 수요량 예측 모형을 제안하였다. 모형의 입력자료 구축을 위하여 종속변수로 월별 시군구 전력수요량을 독립변수로 월별 시군구 충전소 보급대수, 월별 시군구 전기자동차 충전소 충전 횟수, 월별 전기자동차 등록대수 자료를 월 단위로 수집하고 수집된 7년간 자료 중 4년간 자료를 학습기간으로 3년간 자료를 검증 기간으로 적용하였다. 전기자동차 전력 수요량 예측 모형의 정확성을 검증하기위하여 통계적 방법인 Exponential Smoothing(ETS), ARIMA모형의 결과와 비교한 결과 ETS, ARIMA 각각의 오차율은 12%, 21%로 본 논문에서 제시한 ETS가 9% 더 정확하게 분석되었으며, 전기자동차 전력 수요량 예측 모형으로써 적합함을 확인하였다. 향후 이 모형을 이용한 전기자동차 충전소 설치 계획부터 운영관리 측면에서 활용될 것으로 기대한다.

• 대한산업공학회지
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• 제16권2호
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• pp.129-134
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• 1990

Exponential smoothing methods have enjoyed a long history of successful applications and have been used in forecasting for many years. However, it has been long known that one of the deficiencies of the method is an inability to respond quickly to interventions to interruptions, or to large changes in level of the underlying process. An exponential smoothing method adaptive to repeated random level changes is proposed using a change-detection statistic derived from a simple dynamic linear model. The results are compared with Trigg and Leach's and the exponential smoothing methods.