• 제목/요약/키워드: Inverse Estimation

검색결과 458건 처리시간 0.028초

역복사경계해석을 위한 다양한 조정기법 비교 (Comparison of Regularization Techniques For an Inverse Radiation Boundary Analysis)

  • 김기완;백승욱
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2004년도 추계학술대회
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    • pp.1288-1293
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    • 2004
  • Inverse radiation problems are solved for estimating the boundary conditions such as temperature distribution and wall emissivity in axisymmetric absorbing, emitting and scattering medium, given the measured incident radiative heat fluxes. Various regularization methods, such as hybrid genetic algorithm, conjugate-gradient method and Newton method, were adopted to solve the inverse problem, while discussing their features in terms of estimation accuracy and computational efficiency. Additionally, we propose a new combined approach of adopting the genetic algorithm as an initial value selector, whereas using the conjugate-gradient method and Newton method to reduce their dependence on the initial value.

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역복사경계해석을 위한 다양한 조정법 비교 (Comparison of Regularization Techniques for an Inverse Radiation Boundary Analysis)

  • 김기완;신병선;길정기;여권구;백승욱
    • 대한기계학회논문집B
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    • 제29권8호
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    • pp.903-910
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    • 2005
  • Inverse radiation problems are solved for estimating the boundary conditions such as temperature distribution and wall emissivity in axisymmetric absorbing, emitting and scattering medium, given the measured incident radiative heat fluxes. Various regularization methods, such as hybrid genetic algorithm, conjugate-gradient method and finite-difference Newton method, were adopted to solve the inverse problem, while discussing their features in terms of estimation accuracy and computational efficiency. Additionally, we propose a new combined approach that adopts the hybrid genetic algorithm as an initial value selector and uses the finite-difference Newton method as an optimization procedure.

Nonparametric Bayesian estimation on the exponentiated inverse Weibull distribution with record values

  • Seo, Jung In;Kim, Yongku
    • Journal of the Korean Data and Information Science Society
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    • 제25권3호
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    • pp.611-622
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    • 2014
  • The inverse Weibull distribution (IWD) is the complementary Weibull distribution and plays an important role in many application areas. In Bayesian analysis, Soland's method can be considered to avoid computational complexities. One limitation of this approach is that parameters of interest are restricted to a finite number of values. This paper introduce nonparametric Bayesian estimator in the context of record statistics values from the exponentiated inverse Weibull distribution (EIWD). In stead of Soland's conjugate piror, stick-breaking prior is considered and the corresponding Bayesian estimators under the squared error loss function (quadratic loss) and LINEX loss function are obtained and compared with other estimators. The results may be of interest especially when only record values are stored.

Parameter estimation of an extended inverse power Lomax distribution with Type I right censored data

  • Hassan, Amal S.;Nassr, Said G.
    • Communications for Statistical Applications and Methods
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    • 제28권2호
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    • pp.99-118
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    • 2021
  • In this paper, we introduce an extended form of the inverse power Lomax model via Marshall-Olkin approach. We call it the Marshall-Olkin inverse power Lomax (MOIPL) distribution. The four- parameter MOIPL distribution is very flexible which contains some former and new models. Vital properties of the MOIPL distribution are affirmed. Maximum likelihood estimators and approximate confidence intervals are considered under Type I censored samples. Maximum likelihood estimates are evaluated according to simulation study. Bayesian estimators as well as Bayesian credible intervals under symmetric loss function are obtained via Markov chain Monte Carlo (MCMC) approach. Finally, the flexibility of the new model is analyzed by means of two real data sets. It is found that the MOIPL model provides closer fits than some other models based on the selected criteria.

역해석에 의한 열전도율 및 확산율 예측 (Estimation of Thermal Conductivity and Diffusivity by an Inverse Analysis)

  • 나재정;이정민;강경택
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2012년도 제38회 춘계학술대회논문집
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    • pp.397-402
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    • 2012
  • 본 논문에서는 미지의 두 열물성 값인 열전도율과 열확산율을 구하기 위하여 Levenberg-Marquardt 방법에 의한 역해석 기법을 도입하였다. 일차원 열전도 문제에 대하여 연산식을 유도하였으며, 시편에 대하여 두 지점의 온도 및 입력유동의 열유속 측정값을 적용하였다. 예측된 열전도율 및 열확산율은 알려진 그라파이트 시편에 대한 열물성 값과 비교하였으며 그 결과 본 논문에서 제시된 역해석 예측 기법 실험의 유효성이 파악되었다.

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레일리 분포와 역-레일리 분포에 근거한 NHPP 소프트웨어 신뢰성 모형의 개발비용 속성 분석에 관한 연구 (A Study on Development Cost Attributes Analysis of NHPP Software Reliability Model Based on Rayleigh Distribution and Inverse Rayleigh Distribution)

  • 양태진
    • 한국정보전자통신기술학회논문지
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    • 제12권6호
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    • pp.554-560
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    • 2019
  • 본 연구에서는 소프트웨어 신뢰성 분야에서 많이 사용하는 유한고장 NHPP Rayleigh 분포 모형과 NHPP Inverse Rayleigh 분포 모형을 소프트웨어 개발비용 모형에 적용한 후, 개발비용과 최적의 방출시간에 대한 속성을 비교, 분석하였다. 소프트웨어 개발비용의 속성을 분석하기 위하여 소프트웨어 고장시간 자료를 사용하였고, 모수추정은 최우추정법을 적용하였으며, 비선형 방정식은 이분법을 사용하여 계산하였다. 그 결과, Rayleigh 모형이 Inverse Rayleigh 모형보다 소프트웨어 개발비용이 비교적 적고, 소프트웨어 방출시점도 빨라서 상대적으로 우수한 모형임을 확인할 수 있었다. 본 연구를 통하여 기존 연구사례가 없는 Rayleigh 모형과 Inverse Rayleigh 모형의 개발비용 속성을 새롭게 분석하였으며, 더불어 소프트웨어 개발자들이 소프트웨어 신뢰도 향상 방법 및 개발비용의 속성을 탐색하는 데 필요한 기본지침으로 활용할 수 있을 것으로 기대한다.

A hybrid inverse method for small scale parameter estimation of FG nanobeams

  • Darabi, A.;Vosoughi, Ali R.
    • Steel and Composite Structures
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    • 제20권5호
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    • pp.1119-1131
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    • 2016
  • As a first attempt, an inverse hybrid numerical method for small scale parameter estimation of functionally graded (FG) nanobeams using measured frequencies is presented. The governing equations are obtained with the Eringen's nonlocal elasticity assumptions and the first-order shear deformation theory (FSDT). The equations are discretized by using the differential quadrature method (DQM). The discretized equations are transferred from temporal domain to frequency domain and frequencies of the nanobeam are obtained. By applying random error to these frequencies, measured frequencies are generated. The measured frequencies are considered as input data and inversely, the small scale parameter of the beam is obtained by minimizing a defined functional. The functional is defined as root mean square error between the measured frequencies and calculated frequencies by the DQM. Then, the conjugate gradient (CG) optimization method is employed to minimize the functional and the small scale parameter is obtained. Efficiency, convergence and accuracy of the presented hybrid method for small scale parameter estimation of the beams for different applied random error, boundary conditions, length-to-thickness ratio and volume fraction coefficients are demonstrated.

New generalized inverse Weibull distribution for lifetime modeling

  • Khan, Muhammad Shuaib;King, Robert
    • Communications for Statistical Applications and Methods
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    • 제23권2호
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    • pp.147-161
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    • 2016
  • This paper introduces the four parameter new generalized inverse Weibull distribution and investigates the potential usefulness of this model with application to reliability data from engineering studies. The new extended model has upside-down hazard rate function and provides an alternative to existing lifetime distributions. Various structural properties of the new distribution are derived that include explicit expressions for the moments, moment generating function, quantile function and the moments of order statistics. The estimation of model parameters are performed by the method of maximum likelihood and evaluate the performance of maximum likelihood estimation using simulation.

An Empirical Study on Dimension Reduction

  • Suh, Changhee;Lee, Hakbae
    • Journal of the Korean Data Analysis Society
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    • 제20권6호
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    • pp.2733-2746
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    • 2018
  • The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.

베이지안 접근법을 이용한 스프링 피로 수명 파라미터의 역 추정 (Inverse Estimation of Fatigue Life Parameters of Springs Based on the Bayesian Approach)

  • 허찬영;안다운;원준호;최주호
    • 대한기계학회논문집A
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    • 제35권4호
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    • pp.393-400
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    • 2011
  • 본 연구에서는 현장의 축적된 피로 수명 시험 데이터를 바탕으로 유한요소해석(Finite Element Analysis)을 이용하여 스프링의 피로 수명 파라미터를 역 추정(Inverse Estimation)하는 연구를 수행하였다. 베이지안 접근법(Bayesian Approach)을 이용하여 불확실성 피로 수명 파라미터의 사후분포(Posterior distribution)를 구하였고, 마코프체인몬테카를로(Markov Chain Monte Carlo) 기법을 이용하여 역 추정된 파라미터의 샘플 데이터를 생성하였다. 얻어진 샘플링 데이터를 기반으로 피로 수명을 예측한 결과 신뢰 수준 내에서 실제 수명 시험 결과가 예측한 범위 내에 잘 포함되고 있음을 알 수 있었다.