• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.97-113
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• 2017

This paper proposes a method for sufficient dimension reduction (SDR) of mixture data. We consider mixture data containing more than one component that have distinct central subspaces. We adopt an approach of a model-based sliced inverse regression (MSIR) to the mixture data in a simple and intuitive manner. We employed mixture probabilistic principal component analysis (MPPCA) to estimate each central subspaces and cluster the data points. The results from simulation studies and a real data set show that our method is satisfactory to catch appropriate central spaces and is also robust regardless of the number of slices chosen. Discussions about root selection, estimation accuracy, and classification with initial value issues of MPPCA and its related simulation results are also provided.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.5-12
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• 2008

This paper presents the features of an impact angle constrained open-loop optimal trajectory which is given by a function of initial conditions and optimal guidance gains. Using missile motion described by linearized kinematic equations and a proper form of performance index, an inverse optimal problem is suggested to investigate the gains related to the performance index. The flight trajectory and time-to-go can be shaped in terms of the optimal guidance gains. The results are evaluated by 3-DOF simulation.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.2
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• pp.126-131
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• 2001

One of the major obstacles in testing or evaluating precisely the thermal behavior of a machine tool is the difficulty in measuring the heat transfer coefficients on the surfaces by a conventional method. This paper presents a new approach based on the inverse method to identify the values of heat transfer coefficients by using temperature changes measured on the surfaces of a machine tool during a short period in its operating. In the present method, a machine tool structure is modeled by the finite element method and the characteristic curves of the temperature change at several points on machine tool surfaces are theoretically derived in the form that they contain the heat transfer coefficient as an unfixed heat source are approximated so that the theoretical characteristic curves of temperature change fit the measured ones as closely as possible.

• Wind and Structures
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• v.24 no.3
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• pp.249-265
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• 2017

An efficient and accurate algorithm is proposed to estimate flutter safety factor of suspension bridges satisfying prescribed reliability levels. Uncertainties which arise from the basic wind speed at the bridge deck location, critical flutter velocity, the wind conversion factor from a scaled model to the prototype structure and the gust speed factor are incorporated. The proposed algorithm integrates the concepts of the inverse reliability method and the calculation method of the critical flutter velocity of suspension bridges. The unique feature of the proposed method is that it offers a tool for flutter safety assessment of suspension bridges, when the reliability level is specified as a target to be satisfied by the designer. Accuracy and efficiency of this method with reference to three example suspension bridges is studied and numerical results validate its superiority over conventional deterministic method. Finally, the effects of various parameters on the flutter safety factor of suspension bridges are also investigated.

• Structural Engineering and Mechanics
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• v.23 no.2
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• pp.195-207
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• 2006

An efficient and accurate algorithm is proposed to estimate cable safety factor of suspension bridges satisfying prescribed reliability levels. Uncertainties in the structure and load parameters are incorporated. The proposed algorithm integrates the concepts of the inverse reliability method and deterministic method for assessing cable safety factors of suspension bridges. The unique feature of the proposed method is that it offers a tool for cable safety assessment of suspension bridges, when the reliability level is specified as a target to be satisfied by the designer. After the accuracy and efficiency of the method are demonstrated through two numerical examples, the method is used to estimate cable safety factors of suspension bridges with span length ranging from 2000 to 5000 m. The results show that the deterministic method overestimates cable safety factor of suspension bridges because of neglecting the parameter uncertainty effects. The actual cable safety factor of suspension bridges should be estimated based on the proposed method.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.211-216
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• 1997

An inverse method with regularization has been developed to determine the viscoelastic properties of trabecular bone. A series of stress relaxation experiments were performed under the condition of uniaxial compression stress state. Optimization has been formulated within the framework of nonlinear least-squares and a modified Gauss-Newton method with a zeroth-order regularization technique. The stress relaxation behavior of trabecular bone was analyzed using a standard viscoelastic model. The present study clearly shows that trabecular bone exhibits typical viscoelastic stress relaxation behavior, and the obtained material parameters well represent the viscoelastic behavior of trabecular bone.

• Korean Journal of Remote Sensing
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• v.11 no.1
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• pp.19-29
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• 1995

The surface velocities were estimated by the Maximum Cross Correlation(MCC) method and an inverse method from AVHRR/SST. In the results of MCC, discontinuous flow fields were estimated in the case that cross correlation coefficient was above 0.5 but these flow pattern disappeared when cross correlation coefficient was above 0.9. This estimation was conspicuous near SST patterns of eddies. In the results of inverse method, flow field was continuous and eddy motion was estimated definitely but the velocity was overstimated in compared with MCC result over the area of small temperature gradient. This result may be due to temperature error included in SST calculated and spatial variation of heat flux.

• Communications for Statistical Applications and Methods
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• v.28 no.3
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• pp.267-279
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• 2021

A regression with multi-dimensional responses is quite common nowadays in the so-called big data era. In such regression, to relieve the curse of dimension due to high-dimension of responses, the dimension reduction of predictors is essential in analysis. Sufficient dimension reduction provides effective tools for the reduction, but there are few sufficient dimension reduction methodologies for multivariate regression. To fill this gap, we newly propose two fused slice-based inverse regression methods. The proposed approaches are robust to the numbers of clusters or slices and improve the estimation results over existing methods by fusing many kernel matrices. Numerical studies are presented and are compared with existing methods. Real data analysis confirms practical usefulness of the proposed methods.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.247-262
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• 2024

In this paper, we explore nonlinear sufficient dimension reduction (SDR) methods, with a primary focus on establishing a foundational framework that integrates various nonlinear SDR methods. We illustrate the generalized sliced inverse regression (GSIR) and the generalized sliced average variance estimation (GSAVE) which are fitted by the framework. Further, we delve into nonlinear extensions of inverse moments through the kernel trick, specifically examining the kernel sliced inverse regression (KSIR) and kernel canonical correlation analysis (KCCA), and explore their relationships within the established framework. We also briefly explain the nonlinear SDR for functional data. In addition, we present practical aspects such as algorithmic implementations. This paper concludes with remarks on the dimensionality problem of the target function class.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1679-1688
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• 1990

The method of nonlinear parameter estimation(NPE), which is a statistical and an inverse method, is used to estimate the thermal diffusivity of the porous insulation material. In order to apply the NPE method for measuring the thermal diffusivity, and algorithm for programing suitable to IBM personal computer is established, and is studied the statistical treatment of experimental data and theory of estimation. The experimental data obtained by discrete measurement using a constant heat flux technique are used to find the boundary conditions, initial conditions, and the thermal diffusivity, and then the final values are compared with the values obtained by some different methods. The results are presented as follows:(1) NPE method is used to establish the estimation of the thermal diffusivity and compared results with experimental output shows, that this method can be applicable to define the thermal diffusivity without considering hear flux types. (2) Because of all of the temperatures obtained by the discrete measurement on each steps of time are used to estimate the thermal diffusivity. Although some error in the temperature measurements of temperature are included in estimating process, its influences on the final value are minimzed in NPE method. (3) NPE method can reduce the experimental time including the time of data collecting in a few minutes and can take smaller specimen compared with steady state method. If the tube-type furnace is used, also the adjusting time of surrounding temperature can be reduced.