• Title/Summary/Keyword: Two-parameter Approach

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Improving $L_1$ Information Bound in the Presence of a Nuisance Parameter for Median-unbiased Estimators

  • Sung, Nae-Kyung
    • Journal of the Korean Statistical Society
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    • v.22 no.1
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    • pp.1-12
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    • 1993
  • An approach to make the information bound sharper in median-unbiased estimation, based on an analogue of the Cramer-Rao inequality developed by Sung et al. (1990), is introduced for continuous densities with a nuisance parameter by considering information quantities contained both in the parametric function of interest and in the nuisance parameter in a linear fashion. This approach is comparable to that of improving the information bound in mean-unbiased estimation for the case of two unknown parameters. Computation of an optimal weight corresponding to the nuisance parameter is also considered.

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New analysis of nonlinear system with time varying parameter

  • Lee, Seon-Ho;Lim, Jong-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.231-235
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    • 1995
  • In this paper, the frozen time approach is used to analyze the nonlinear system with time varying parameter. Using the extended linearization, we propose two analytical methods that compute an upper bound of the Euclidean norm of the difference between state variable and equilibrium point of the given system. The propertise of the two methods are discussed with simple examples.

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The effect of carbon nanotubes agglomeration on vibrational response of thick functionally graded sandwich plates

  • Tahouneh, Vahid
    • Steel and Composite Structures
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    • v.24 no.6
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    • pp.711-726
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    • 2017
  • In the present work, by considering the agglomeration effect of single-walled carbon nanotubes, free vibration characteristics of functionally graded (FG) nanocomposite sandwich plates resting on Pasternak foundation are presented. The volume fractions of randomly oriented agglomerated single-walled carbon nanotubes (SWCNTs) are assumed to be graded in the thickness direction. To determine the effect of CNT agglomeration on the elastic properties of CNT-reinforced composites, a two-parameter micromechanical model of agglomeration is employed. In this research work, an equivalent continuum model based on the Eshelby-Mori-Tanaka approach is employed to estimate the effective constitutive law of the elastic isotropic medium (matrix) with oriented straight CNTs. The 2-D generalized differential quadrature method (GDQM) as an efficient and accurate numerical tool is used to discretize the equations of motion and to implement the various boundary conditions. The proposed rectangular plates have two opposite edges simply supported, while all possible combinations of free, simply supported and clamped boundary conditions are applied to the other two edges. The benefit of using the considered power-law distribution is to illustrate and present useful results arising from symmetric and asymmetric profiles. The effects of two-parameter elastic foundation modulus, geometrical and material parameters together with the boundary conditions on the frequency parameters of the laminated FG nanocomposite plates are investigated. It is shown that the natural frequencies of structure are seriously affected by the influence of CNTs agglomeration. This study serves as a benchmark for assessing the validity of numerical methods or two-dimensional theories used to analysis of laminated plates.

Estimation of Defect Clustering Parameter Using Markov Chain Monte Carlo (Markov Chain Monte Carlo를 이용한 반도체 결함 클러스터링 파라미터의 추정)

  • Ha, Chung-Hun;Chang, Jun-Hyun;Kim, Joon-Hyun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.3
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    • pp.99-109
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    • 2009
  • Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

Design and behavior of two profiles for structural performance of composite structure: A fluid interaction

  • Thobiani, Faisal Al;Hussain, Muzamal;Khadimallah, Mohamed Amine;Ghandourah, Emad;Alhawsawi, Abdulsalam;Alshoaibi, Adil
    • Steel and Composite Structures
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    • v.43 no.2
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    • pp.221-228
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    • 2022
  • Two-dimensional stagnation point slip flow of a Casson fluid impinging normally on a flat linearly shrinking surface is considered. The modeled PDEs are changed into nonlinear ODEs through appropriate nonlinear transformations.The flow is assumed to be steady and incompressible, with external magnetic field acting on it. Similarity transformation is utilized to investigate the behavior of many parameters for heat and velocity distributions using truncation approach.The influence of buoyancy parameter, slip parameter, shrinking parameter, Casson fluid parameter on the heat profile. The effect of the magnetic parameter on the streamwise velocity profile is also investigated.

Various types of modelling for scale parameter in Weibull intensity function for two-dimensional warranty data

  • Baik, Jai-Wook;Jo, Jin-Nam
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.3
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    • pp.555-560
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    • 2010
  • One-dimensional approach to two-dimensional warranty data involves modeling us- age as a function of time. Iskandar (1993) suggests a simple linear model for usage. However, simple linear form of intensity function is of limited value to model the situa-tion where the intensity varies over time. In this study Weibull intensity is considered where the scale parameter is expressed in terms of different models. We will nd out how each parameter in the model a ects the warranty cost and which model gives a bigger number of failures within the two-dimensional warranty region.

Determination of Vibration Parameters Using The Improved Time Domain Modal Identification Algorithm (개선된 시간영역 해석기법에 의한 동특성 추정)

  • Jung, Beom-Seok
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.3 no.2
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    • pp.147-154
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    • 1999
  • A new approach to conducting the vibration parameters identification algorithm is proposed. The approach employs the concept of modal amplitude ratio implemented in a mode shape estimation. The accuracy of the improved Ibrahim Time Domain identification algorithm in extracting structural modal parameters from free response functions has been studied using computer simulated data for 9 stations on the two-span continuous beam. Simulated responses from the lumped and distributed parameter system demonstrate that this algorithm produces excellent results, even in the 300% noise response.

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An alternative procedure for parameter design using desirability function in combined array (통합배열에서 기대함수를 이용한 파라미터설계 대체방안)

  • Kwon, Yong Man
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1263-1272
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    • 2016
  • Product array approach which is used in the Taguchi parameter design has a number of advantages by considering the noise factor. However, a disadvantage of this method is that it requires an excessively large number of experiments. So combined array approach have been proposed to reduce the number of experiments. Taguchi has used the signal-to-noise ratio to find the optimum conditions in the Taguchi parameter design. In analyzing the data from the parameter design various problems tends occur by using an SN. In this paper, we propose an alternative solution for reducing the number of experiments without depending on the signal-to-noise ratio to overcome the shortcomings of the parameter design. Two examples illustrate this procedure in the two different experimental design (product array, combined array) approaches.

A lumped parameter method of characteristics approach and multigroup kernels applied to the subgroup self-shielding calculation in MPACT

  • Stimpson, Shane;Liu, Yuxuan;Collins, Benjamin;Clarno, Kevin
    • Nuclear Engineering and Technology
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    • v.49 no.6
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    • pp.1240-1249
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    • 2017
  • An essential component of the neutron transport solver is the resonance self-shielding calculation used to determine equivalence cross sections. The neutron transport code, MPACT, is currently using the subgroup self-shielding method, in which the method of characteristics (MOC) is used to solve purely absorbing fixed-source problems. Recent efforts incorporating multigroup kernels to the MOC solvers in MPACT have reduced runtime by roughly $2{\times}$. Applying the same concepts for self-shielding and developing a novel lumped parameter approach to MOC, substantial improvements have also been made to the self-shielding computational efficiency without sacrificing any accuracy. These new multigroup and lumped parameter capabilities have been demonstrated on two test cases: (1) a single lattice with quarter symmetry known as VERA (Virtual Environment for Reactor Applications) Progression Problem 2a and (2) a two-dimensional quarter-core slice known as Problem 5a-2D. From these cases, self-shielding computational time was reduced by roughly $3-4{\times}$, with a corresponding 15-20% increase in overall memory burden. An azimuthal angle sensitivity study also shows that only half as many angles are needed, yielding an additional speedup of $2{\times}$. In total, the improvements yield roughly a $7-8{\times}$ speedup. Given these performance benefits, these approaches have been adopted as the default in MPACT.

A Constructive Algorithm of Fuzzy Model for Nonlinear System Modeling (비선형 시스템 모델링을 위한 퍼지 모델 구성 알고리즘)

  • Choi, Jong-Soo
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.648-650
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    • 1998
  • This paper proposes a constructive algorithm for generating the Takagi-Sugeno type fuzzy model through the sequential learning from training data set. The proposed algorithm has a two-stage learning scheme that performs both structure and parameter learning simultaneously. The structure learning constructs fuzzy model using two growth criteria to assign new fuzzy rules for given observation data. The parameter learning adjusts the parameters of existing fuzzy rules using the LMS rule. To evaluate the performance of the proposed fuzzy modeling approach, well-known benchmark is used in simulation and compares it with other modeling approaches.

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