• Structural Engineering and Mechanics
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• 제32권1호
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• pp.55-69
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• 2009

A quasi ideal importance sampling simulation method combined in the conditional expectation is proposed for the structural reliability estimation. The quasi ideal importance sampling joint probability density function (p.d.f.) is so composed on the basis of the ideal importance sampling concept as to be proportional to the conditional failure probability multiplied by the p.d.f. of the sampling variables. The respective marginal p.d.f.s of the ideal importance sampling joint p.d.f. are determined numerically by the simulations and partly by the piecewise integrations. The quasi ideal importance sampling simulations combined in the conditional expectation are executed to estimate the failure probabilities of structures with multiple failure surfaces and it is shown that the proposed method gives accurate estimations efficiently.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1765-1770
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• 2005

Recently, particle filters have attracted attentions for nonlinear state estimation. In this approaches, a posterior probability distribution of the state variable is evaluated based on observations in simulation using so-called importance sampling. We proposed a new filter, Evolution Strategies based particle (ESP) filter to circumvent degeneracy phenomena in the importance weights, which deteriorates the filter performance, and apply it to simultaneous state and parameter estimation of nonlinear state space models. Results of numerical simulation studies illustrate the applicability of this approach.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2001년도 학술대회지
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• pp.291-294
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• 2001

This study has established an appraisal standard to select VE subject when they evaluate of design VE by using of a qualify model in an early design step and has suggested an improvement method for importance's estimation method of an appraisal standard. An importance's estimation method is to arrangement of geometric average method using an AHP method to this study, When an evaluation of a quality model, we estimate an importance by establishing of an appraisal standard of economics, construction, security, environmental influence, maintenance, etc.

• 한국임상약학회지
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• 제23권2호
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• pp.137-141
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• 2013

Purpose: This study compared the performance of new NONMEM estimation methods using a population analysis dataset collected from a clinical study that consisted of 40 individuals and 567 observations after a single oral dose of glimepiride. Method: The NONMEM 7.2 estimation methods tested were first-order conditional estimation with interaction (FOCEI), importance sampling (IMP), importance sampling assisted by mode a posteriori (IMPMAP), iterative two stage (ITS), stochastic approximation expectation-maximization (SAEM), and Markov chain Monte Carlo Bayesian (BAYES) using a two-compartment open model. Results: The parameters estimated by IMP, IMPMAP, ITS, SAEM, and BAYES were similar to those estimated using FOCEI, and the objective function value (OFV) for diagnosing the model criteria was significantly decreased in FOCEI, IMPMAP, SAEM, and BAYES in comparison with IMP. Parameter precision in terms of the estimated standard error was estimated precisely with FOCEI, IMP, IMPMAP, and BAYES. The run time for the model analysis was shortest with BAYES. Conclusion: In conclusion, the new estimation methods in NONMEM 7.2 performed similarly in terms of parameter estimation, but the results in terms of parameter precision and model run times using BAYES were most suitable for analyzing this dataset.

• 정보처리학회논문지B
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• 제15B권5호
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• pp.487-492
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• 2008

대부분의 웹 검색엔진은 문서의 적합도와 중요도를 함께 고려하는 순위화 방법을 사용한다. 문서의 적합도는 문서가 사용자의 검색의도를 만족시키는 정도이고, 중요도는 인기 있거나 양질의 내용을 포함하는 등 문서의 품질을 표시하는 정도라고 할 수 있다. 지금까지 웹 문서의 중요도를 평가하는 방법으로 가장 성공적인 것은 하이퍼링크 구조를 사용한 방법이다. 하지만 블로그의 경우, 해당 블로그를 작성한 블로거와 그 블로거가 소유하는 다른 문서들을 알 수 있기 때문에 문서의 중요도를 평가하는 다른 방법을 생각할 수 있다. 본 논문에서 제안하는 방법은 사용자의 북마크와 클릭를 이용하여 문서의 중요도를 계산하고, 그러한 문서 점수를 바탕으로 블로거의 구루점수를 계산한다. 마지막으로 문서를 순위화할 때 해당 문서를 작성한 구루의 구루 점수를 반영한다. 이렇게 되면 구루점수가 높은 구루 블로거의 문서들이 상위에 검색됨에 따라서 전반적으로 검색 품질이 개선될 수 있다. 블로그 문서를 대상으로 한 실험결과 제안하는 방법이 기존의 전통적인 웹 검색 성능과 비교하여 정답집합과의 연관성이 높음을 알 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.559-564
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• 2003

Recently, particle filters have attracted attentions for nonlinear state estimation. They evaluate a posterior probability distribution of the state variable based on observations in simulation using so-called importance sampling. However, degeneracy phenomena in the importance weights deteriorate the filter performance. A new filter, Evolution Strategies Based Particle Filter, is proposed to circumvent this difficulty and to improve the performance. Numerical simulation results illustrate the applicability of the proposed idea.

• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.381-397
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• 2004

The marginal likelihood has become an important tool for model selection in Bayesian analysis because it can be used to rank the models. We discuss the marginal likelihood for Poisson regression models that are potentially useful in small area estimation. Computation in these models is intensive and it requires an implementation of Markov chain Monte Carlo (MCMC) methods. Using importance sampling and multivariate density estimation, we demonstrate a computation of the marginal likelihood through an output analysis from an MCMC sampler.

• 한국안전학회지
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• 제10권2호
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• pp.10-16
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• 1995

In estimating the fatigue data, only the uniform safety rate has been applied so far However, since more reasonable design concepts such as machine structures or subsidiary materials will be required in the future, the importance of a statistical estimation method for fatigue data is being highlighted. With such basic conception in mind, this study was aimed at critically discussing the interval estimation method which has been applied using the classical statistics thus far It was conceived that this conventional method would result in the estimation of the unstable side from the viewpoint of the likelihood Interval estimation method. In this regard, this study aimed at estimating the fatigue strength through the likelihood interval estimation method comparing it with the conventional interval estimation method would result in the estimation of the unstable side from the viewpoint of the likelihood interval estimation method. One of the methods using the likelihood for estimation data is the Bayes method. Based on this theory, statistical estimations were positivly applied, and thereupon, the fatigue data were estimated.

• 한국지리정보학회지
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• 제19권1호
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• pp.167-179
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• 2016

최근 범지구적으로 증가하는 이상기후에 의해 SOC 시설물 안전이 지속적으로 위협받고 있다. 재난대응을 위해서는 피난 대피 경로 제시 등과 같은 신속한 의사결정이 필요하며 이는 재난 재해 정보 및 SOC 시설물 정보가 융 복합된 시공간적 정보가 활용되어야 한다. 이러한 정보는 정부 및 유관기관에서 분산적으로 수집되고 있어, 통합적 관리가 이루어지지 않고 있는 실정이다. 신속한 재난대응을 위해서는 분산 수집 관리되고 있는 재난 재해 정보의 통합관리와 SOC 시설물에 대한 안전도와 피해도 등의 정보 생성이 필요하다. 또한 재난 재해 정보 특성상 시공간적 융합이 필요하기 때문에, 관련 정보를 통합한 재해대응 의사결정 지원을 위한 인벤토리 구축이 필요하다. 본 연구에서는 신속한 재난대응의사결정 지원을 위한 시설물 중요도 위험도 피해액 인벤토리 구축 방안을 제시한다. 본 연구를 통해 분산 관리 되고 있는 재난 재해 및 SOC 시설물 관련 데이터를 수집하여 표준화 하고, 시설물의 중요도 위험도 피해액 산정에 필요한 통합 정보를 제공 할 수 있다. 향후 제안된 시스템을 통해 선제적 재난 대응을 위한 의사결정 도구로 활용할 수 있을 것으로 판단된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권5호
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• pp.1356-1376
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• 2023

Software effort estimation is one of the most difficult tasks in software development whereas predictability is also of equal importance for strategic management. Accurate prediction of the actual cost that will be incurred in software development can be very beneficial for the strategic management. This study discusses the latest trends in software estimation focusing on analogy-based techniques to show how they have improved the accuracy for software effort estimation. It applies the standard deviation technique to the expected value of analogy-based estimates to improve accuracy. In more than 60 percent cases the applied technique of this study helped in improving the accuracy of software estimation by reducing the Magnitude of Relative Error (MRE). The technique is simple and it calculates the expected value of cost or time and then uses different confidence levels which help in making more accurate commitments to the customers.