• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.43-50
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• 2001

In this paper, we propose the design procedure of advance Polynomial Neural Networks(PNN) architecture for optimal model identification of complex and nonlinear system. The proposed PNN architecture is presented as the generic and advanced type. The essence of the design procedure dwells on the Group Method of Data Handling(GMDH). PNN is a flexible neural architecture whose structure is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but is generated in a dynamic way. In this sense, PNN is a self-organizing network. With the aid of three representative numerical examples, compari-sons show that the proposed advanced PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and generalization capabilities of model is evaluated and also discussed.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.49-59
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• 2012

In computer simulation models the output from the computer code is often deterministic, i.e., running the code twice with the same values for the input variables would give the same output. It is discussed why the response surface method with polynomial approximation for the true response function is a good approximation to the computer experiments model. A sequential strategy to find the proper reduced quadratic polynomial model is illustrated with a case study in the military war game computer simulation model.

• Bulletin of the Korean Mathematical Society
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• v.39 no.4
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• pp.687-704
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• 2002

We show that the class of inner chordarc domains is properly contained in the class of exterior quasiconvex domains. We also show that the class of exterior quasiconvex domains is properly contained in the class of John disks. We give the conditions which make the converses of the above results be true. Next , we show that an exterior quasiconvex domain satisfies certain growth conditions for the exterior Riemann mapping. From the results we show that the domain satisfies the Bernstein inequality and the integrated version of it. Finally, we assume that f is a function which is continuous in the closure of a domain D and analytic in D. We show connections between the smoothness of f and the rate at which it can be approximated by polynomials on an exterior quasiconvex domain and a $Lip_\alpha$-extension domain.

• Steel and Composite Structures
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• v.7 no.6
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• pp.441-456
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• 2007

In literature for thin-walled sections with L, [, +, I, and ${\Box}$- shapes the approximate torsion equations for stiffness are used which were proposed by Bach (Hsu 1984), p.30. New formulae for torsional stiffness of bars with L, [, +, I, and ${\Box}$ cross section valid not only for thin-walled sections are presented in this paper. These formulae are obtained by appropriate polynomial approximation of stiffness results obtained by means of method of fundamental solutions. On the base of obtained results the validity of Bach's formulae are verified when cross section is not thin-walled.

• The KIPS Transactions:PartA
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• v.18A no.2
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• pp.69-74
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• 2011

The minimum dominating set problem of a graph G is to find a smallest possible dominating set. The minimum dominating set problem is a well-known NP-complete problem such that it cannot be solved in polynomial time. Heuristic or approximation algorithm, however, will perform well in certain area of application. In this paper, we suggest three different simulated annealing algorithms and experimentally show better efficiency improvement by applying these algorithms to the graph instances developed by DIMACS.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.383-392
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• 2010

Modelling financial phenomena with diffusion processes is frequently used technique. This study reviews the earlier researches on the approximation problem of transition densities of diffusion processes, which takes important roles in estimating diffusion processes, and consider the method to obtain the coefficients of series efficiently, in series approximation method of transition densities. We developed a new efficient algorithm to compute the coefficients which are represented by repeated Dynkin operator on Hermite polynomial.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.443-450
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• 2016

This paper deals with a kind of packing problem of which the goal is to compose one or more templates which will be used to produce the items of different types. Each template consists of a fixed number of slots which are assigned to the different types of items and the production of the items is accomplished by printing the template repeatedly. The objective is to minimize the total number of produced items. This problem is known to be NP-hard. We present a polynomial time approximation algorithm which has a constant approximation ratio. The proposed algorithm is based on the well-known first-fit strategy.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.948-955
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• 1987

The model reduction method of the high order linear time invariant systems is proposed. The continuous fraction expansion of Auxiliary denominator polynomial is used to obtain denominator polynomial of the reduced order model, and the numerator polynomial of the reduced order model is obtained by equating the first some moments of the original and the reduced order model, using simplified moment function. This methiod does not require the calculation of the reciprocal transformation which should be calculated in Routh approximation, furthemore the stability of the reduced order model is guaranted if original system is stable. Responses of this method showed us good characteristics.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.2
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• pp.67-85
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• 2013

Reproducing Polynomial Particle Method (RPPM) is one of meshless methods that use meshes minimally or do not use meshes at all. In this paper, the RPPM is employed for free vibration analysis of shear-deformable plates of the first order shear deformation model (FSDT), called Reissner-Mindlin plate. For numerical implementation, we use flat-top partition of unity functions, introduced by Oh et al, and patchwise RPPM in which approximation functions have high order polynomial reproducing property and the Kronecker delta property. Also, we demonstrate that our method is highly effective than other existing results for various aspect ratios and boundary conditions.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2863-2865
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• 1999

In this paper we present the modeling of ozone prediction system using polynomial neural network. The Polynomial Neural Network is a useful tool for data learning, nonlinear function estimation and prediction of dynamic system. The mechanism of ozone concentration is highly complex, nonlinear, nonstationary. The purposed method shows that the prediction to the ozone concentration based upon a polynomial neural network gives us a good performance for ozone prediction with ability of superior data approximation.