• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.141-151
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• 2010

Hybrid fuzzy regression analysis is used for integrating randomness and fuzziness into a regression model. Least squares support vector machine(LS-SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate hybrid fuzzy linear and nonlinear regression models with crisp inputs and fuzzy output using weighted fuzzy arithmetic(WFA) and LS-SVM. LS-SVM allows us to perform fuzzy nonlinear regression analysis by constructing a fuzzy linear regression function in a high dimensional feature space. The proposed method is not computationally expensive since its solution is obtained from a simple linear equation system. In particular, this method is a very attractive approach to modeling nonlinear data, and is nonparametric method in the sense that we do not have to assume the underlying model function for fuzzy nonlinear regression model with crisp inputs and fuzzy output. Experimental results are then presented which indicate the performance of this method.

• Korean Journal of Optics and Photonics
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• v.11 no.1
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• pp.25-32
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• 2000

Comparisons are made between the first hyperpolarizability $\beta$ of pure N-(4-nitrophenyl)-(L)-prolinol (NPP) and poly (methyl metacrylate) (PMMA) or poly-p-(phenylene terephthalates) (PPT) with NPP side group determined with two different methods, electric-field-induced second-harmonic generation (EFISHG) and hyper-Rayleigh scattering (HRS) methods. Both techniques yield the same values within the experimental errors for pure NPP and NPP-PMMA in 1,1,2,2-tetrachloroethane solution. But the measured results of NPP-PPT polymer in 1,1,2,2-tetrachloroethane solution are showing that the first hyperpolarizability was enhanced with an enhencement of a factor 9.7 in EFISHG and a factor 2.4 in HRS relative to pure NPP. These results indicate that nonlinear optical chromophores organized as side groups of polymers with a rigid backbone contribute coherently to the secondorder nonlinear response of the polymer in the dc electric field as polar polymer chains. hains.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.896-902
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• 2016

In this paper, we investigate a minimum mean-squared error based nonlinear successive precoding method as a practical solution of dirty paper coding for multiuser downlink channels where each user has more than one antenna in the presence of other cell interference (OCI). Unlike conventional zero-forcing (ZF) based methods, the proposed scheme takes the OCI plus noise into account when suppressing the inter-cell multiuser interference, which results in improvement of the received signal-to-interference-plus-noise ratio. Simulation results show that the proposed scheme outperforms conventional methods in terms of sum rate for various OCI configurations.

• Journal of Ship and Ocean Technology
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• v.9 no.4
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• pp.35-46
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• 2005

The performance of optimisation methods, based on penalty functions, is highly problem- dependent and many methods require additional tuning of some variables. This additional tuning is the influences of penalty coefficient, which depend strongly on the degree of constraint violation. Moreover, Binary-coded Genetic Algorithm (BGA) meets certain difficulties when dealing with continuous and/or discrete search spaces with large dimensions. With the above reasons, Real-coded Micro-Genetic Algorithm (R$\mu$GA) is proposed to find the global optimum of continuous and/or discrete nonlinear constrained engineering problems without handling any of penalty functions. R$\mu$GA can help in avoiding the premature convergence and search for global solution-spaces, because of its wide spread applicability, global perspective and inherent parallelism. The proposed R$\mu$GA approach has been demonstrated by solving three different engineering design problems. From the simulation results, it has been concluded that R$\mu$GA is an effective global optimisation tool for solving continuous and/or discrete nonlinear constrained real­world optimisation problems.

• Industrial Engineering and Management Systems
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• v.12 no.3
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• pp.244-253
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• 2013

In industries, shipping is an important issue in improving the forecasting accuracy of sales. This paper introduces a hybrid method and plural methods are compared. Focusing the equation of exponential smoothing method (ESM) that is equivalent to (1, 1) order autoregressive-moving-average (ARMA) model equation, a new method of estimating the smoothing constant in ESM had been proposed previously by us which satisfies minimum variance of forecasting error. Generally, the smoothing constant is selected arbitrarily. However, this paper utilizes the above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate the smoothing constant. Thus, theoretical solution is derived in a simple way and it may be utilized in various fields. Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. This method is executed in the following method. Trend removing by the combination of linear and 2nd order nonlinear function and 3rd order nonlinear function is executed to the original production data of two kinds of bread. Genetic algorithm is utilized to search the optimal weight for the weighting parameters of linear and nonlinear function. For comparison, the monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non-monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful for the time series that has various trend characteristics and has rather strong seasonal trend. The effectiveness of this method should be examined in various cases.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.3 s.108
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• pp.263-269
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• 2006

The objective of the present work is to develop a time-domain numerical method of broadband noise in a cascade of airfoils. This paper focuses on dipolar broadband noise sources, resulting from the interaction of turbulent inflows with the flat-plate airfoil cascade. The turbulence response of a two-dimensional cascade is studied by solving both of the linearised and the full nonlinear Euler equations employing accurate higher order spatial differencing, time stepping techniques and non-reflecting inflow/outflow boundary condition. The time-domain result using the linearised Euler equations shows good agreement with the analytical solution using the modified LINSUB code. Through the comparison of the nonlinear time-domain result using the full nonlinear Euler equations with the linear, it is found that the acoustic mode amplitude of the nonlinear response is less than that of the linear response due to the energy cascade from low frequency components to the high frequency ones. Considering the merits of the time-domain methods over the typical time-linearised frequency-domain analysis, the current method is expected to be promising tools for analyzing the effects of the airfoil shapes, non-uniform background flow, linear-nonliear regimes on the broadband noise due to turbulence-cascade interaction.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.812-817
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• 2005

The objective of the present work is to develop a time-domain numerical method of broadband noise in a cascade of airfoils. This paper focuses on dipole broadband noise sources, resulting from the interaction of turbulent inflows with the flat-plate airfoil cascade. The turbulence response of a two-dimensional cascade is studied by solving both of the linearised and full nonlinear Euler equations employing accurate higher order spatial differencing, time stepping techniques and non-reflecting inflow/outflow boundary condition. The time-domain result using the linearised Euler equations shows good agreement with the analytical solution using the modified LINSUB code. Through the comparison of the nonlinear time-domain result using the full nonlinear Euler equations with the linear, it is found that the acoustic mode amplitude of the nonlinear response is less than that of the linear response due to the energy cascade from low frequency components to the high frequency ones. Considering the merits of the time-domain methods over the typical time-linearised frequency-domain analysis, the current method is expected to be promising tools for analyzing the effects of the airfoil shapes, non-uniform background flow, linear-nonliear regimes on the broadband noise due to gust-cascade interaction.

• Communications of the Korean Mathematical Society
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• v.26 no.4
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• pp.709-720
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• 2011

We obtain special type of differential equations which their solution are random variable with known continuous density function. Stochastic differential equations (SDE) of continuous distributions are determined by the Fokker-Planck theorem. We approximate solution of differential equation with numerical methods such as: the Euler-Maruyama and ten stages explicit Runge-Kutta method, and analysis error prediction statistically. Numerical results, show the performance of the Rung-Kutta method with respect to the Euler-Maruyama. The exponential two parameters, exponential, normal, uniform, beta, gamma and Parreto distributions are considered in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.988-991
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• 1996

The purpose of this thesis is to develop methods of designing robust LQR/LQG controllers for time-varying systems with real parametric uncertainties. Controller design that meet desired performance and robust specifications is one of the most important unsolved problems in control engineering. We propose a new framework to solve these problems using Linear Matrix Inequalities (LMls) which have gained much attention in recent years, for their computational tractability and usefulness in control engineering. In Robust LQR case, the formulation of LMI based problem is straightforward and we can say that the obtained solution is the global optimum because the transformed problem is convex. In Robust LQG case, the formulation is difficult because the objective function and constraint are all nonlinear, therefore these are not treatable directly by LMI. We propose a sequential solving method which consist of a block-diagonal approach and a full-block approach. Block-diagonal approach gives a conservative solution and it is used as a initial guess for a full-block approach. In full-block approach two LMIs are solved sequentially in iterative manner. Because this algorithm must be solved iteratively, the obtained solution may not be globally optimal.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.17-30
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• 1997

In this work we approximate the solution of initialboun-dary value problem using a Galerkin-finite element method for the spatial discretization and Implicit Runge-Kutta method for the spatial discretization and implicit Runge-Kutta methods for the time stepping. To deal with the nonlinear term f(x, t, u), we introduce the well-known extrapolation sheme which was used widely to prove the convergence in $L_2$-norm. We present computational results showing that the optimal order of convergence arising under $L_2$-norm will be preserved in $L_{\infty}$-norm.