• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.211-225
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• 2014

A new class of smoothing functions is introduced in this paper, which includes some important smoothing complementarity functions as its special cases. Based on this new smoothing function, we proposed a smoothing Newton method. Our algorithm needs only to solve one linear system of equations. Without requiring the nonemptyness and boundedness of the solution set, the proposed algorithm is proved to be globally convergent. Numerical results indicate that the smoothing Newton method based on the new proposed class of smoothing functions with ${\theta}{\in}(0,1)$ seems to have better numerical performance than those based on some other important smoothing functions, which also demonstrate that our algorithm is promising.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.44-50
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• 2008

Focusing on the exponential smoothing method equivalent to (1, 1) order ARMA model equation, a new method of estimating smoothing constant using exponential smoothing method is proposed. This study goes beyond the usual method of arbitrarily selecting a smoothing constant. First, an estimation of the ARMA model parameter was made and then, the smoothing constants. The empirical example shows that the theoretical solution satisfies minimum variance of forecasting error. The new method was also applied to the stock market price of electrical machinery industry (6 major companies in Japan) and forecasting was accomplished. Comparing the results of the two methods, the new method appears to be better than the ARIMA model. The result of the new method is apparently good in 4 company data and is nearly the same in 2 company data. The example provided shows that the new method is much simpler to handle than ARIMA model. Therefore, the proposed method would be better in these general cases. The effectiveness of this method should be examined in various cases.

• International Journal of Contents
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• v.5 no.4
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• pp.1-6
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• 2009

In this paper, we propose a mesh smoothing method for mesh models with noise. The proposed method enables not only the removal of noise from the vertexes but the preservation and smoothing of shape recognized as edges and comers. The magnitude ratio of 2D area and 3D volume in mesh data is adopted for the smoothing of noise. Comparing with previous smoothing methods, this method does not need many iteration of the smoothing process and could preserve the shape of original model. Experimental results demonstrate improved performance of the proposed approach in 3D mesh smoothing.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.5 no.1
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• pp.11-24
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• 2001

We introduce an assumption about smoothing operator for mixed formulations and show that convergence of Multigrid method for the mixed finite element formulation for the Linear Elasticity. And we show that Richardson and Kaczmarz smoothing satisfy this assumption.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.185-192
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• 1997

We propose a method of paramete estimation using order-of-magnitude analysis for optimal boundary smoothing in Mean Field Annealing(MFA) technique in this paper. We previously proposed two boundary smoothing methods for consistent object representation in the previous paper, one is using a constratined regulaization(CR) method and the other is using a MFA method. The CR method causes unnecessary smoothing effects at corners. On the other hand, the MFA method method smooths our the noise without losing sharpness of corners. The MFA algorithm is influenced by several parameters such as standard deviation of the noise, the relativemagnitude of prior ter, initial temperature and final temperature. We propose a general parameter esimation method for optimal boundary smoothing using order-of-magnitude analysis to be used for consistent object representation in this paper. In addition, we prove the effectiveness of our parameter estimation and also show the temperature parameter sensitivities of the algorithm.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.945-953
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• 2007

In this paper, we propose a smoothing and thus noise-reducing method of data sequences for stock price prediction with hidden Markov models, HMMs. The suggested method just uses simple moving average. A proper average size is obtained from forecasting experiments with stock prices of bank sector of Korean Exchange. Forecasting method with HMM and moving average smoothing is compared with a conventional method.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.618-621
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• 2008

In this paper a new smoothing method of unstructured viscous grid which can be useful when the ALM(Advacning Layer Method) method is used to generate volume grids of prism cells starting with unstructured triangular surface grids. According to the new method two layers of prism cells in the advancing direction which are found by the vector smoothing method are first generated, and then the position of nodes along the middle layer are adjusted by using spring analogy. It is found that the proposed method improves grid quality of the unstructured viscous volume grids for body shape with convex and concave corners.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.257-263
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• 2009

Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent to (1, 1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Theoretical solution was derived in a simple way. Mere application of ESM does not make good forecasting accuracy for the time series which has non-linear trend and/or trend by month. A new method to cope with this issue is required. In this paper, combining the trend removal method with this method, we aim to improve forecasting accuracy. An approach to this method is executed in the following method. Trend removal by a linear function is applied to the original shipping data of consumer goods. The combination of linear and non-linear function is also introduced in trend removal. For the comparison, 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 especially for the time series that has stable characteristics and has rather strong seasonal trend and also the case that has non-linear trend. The effectiveness of this method should be examined in various cases.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.331-334
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• 2003

In the finite element simulation of hot forging processes using hexahedron, remeshing of a flash is very difficult. The mesh compression method is a remeshing technique to construct an effective hexahedral mesh. However, because mesh is distorted during the compression procedure or the mesh compression method, mesh smoothing is necessary to improve the mesh Qualify. in this study, several geometric mesh smoothing techniques and a matrix norm optimization technique are applied and compared which is more adaptive to the mesh compression method.

• Journal of the Korean Geographical Society
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• v.49 no.3
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• pp.339-356
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• 2014

Easy access to DEMs and the development of technology treating DEMs make it easier to extract stream longitudinal profiles from DEMs than previously done. Since such profiles possess many problems such as artificial flats and steps, it should be required for them to be smoothed like natural profiles to estimate gradient values along those sections. However smoothing itself comes with much distortion of raw profile from original DEMs. There has been no research evaluating quantitatively the effects due to smoothing process. Here we attempt to quantify the effects of major smoothing methods on raw and real profiles, suggest a new method to overcome the limitations of them, and evaluate it. This study not only suggests a new smoothing method, but also provides a guideline for choosing a proper smoothing method.