• Asian Journal of Business Environment
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• 제7권3호
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• pp.33-43
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• 2017

Purpose - It is necessary to identify the level of marketing activities of the businesses that are recognized and carried out by the small and midsize businesses that have been supported by the government's small-business policy Research design, data, and methodology - The method of data analysis of this study was conducted by the researcher's acquaintances and center staffs who visited small business owners in a small - scale company operating a business. Results - It is found that the financial support part of the support programs for the small business owners is not related to the center affection among the support programs for the small business owners of the government. This is a fact-finding process that can be regarded as a forming process that has a significant effect on. As a result of the analysis, both marketing activity and center attachment were found to be possible parameters which have significant influence on business performance. Conclusions - Developing a variety of contact and customer management programs with small business owners in the field has enabled the government's policies to effectively penetrate the site, and these efforts eventually resulted in more business results for small business owners.

• 소성∙가공
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• 제27권1호
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• pp.18-27
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• 2018

As one of the functional metal parts in steam turbine diaphragm assembly, the hollow-partitioned turbine nozzle (stator) has large and thick geometries, as well as an asymmetric configuration. Therefore it is hard to support a metal blank in the die cavity. To ease this situation and control posture and position of metal blank (workpiece), a blank support structure is newly introduced. The blank support structure is basically composed of enlarged arms from the blank, guide pins and linear bearings. It can help to control the intermediate blank without a critical sliding phenomenon. The operation mechanism of this blank support structure, during thick plate forming for the hollow-partitioned turbine nozzle stator, is first evaluated. A series of FEM-based numerical simulations, with respect to the width of the guide arm as geometric design parameters, are carried out to investigate its applicable range. As the results, it is observed the blank support structure for this thick plate forming can guide the workpiece to have stable posture during the plate forming process.

• 대한금속재료학회지
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• 제56권11호
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• pp.813-821
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• 2018

The basic oxygen furnace (BOF) steelmaking process in the steel industry is highly complicated, and subject to variations in raw material composition. During the BOF steelmaking process, it is essential to maintain the carbon content and the endpoint temperature at their set points in the liquid steel. This paper presents intelligent models used to estimate the endpoint temperature in the basic oxygen furnace (BOF) steelmaking process. An artificial neural network (ANN) model and a least-squares support vector machine (LSSVM) model are proposed and their estimation performance compared. The classical partial least-squares (PLS) method was also compared with the others. Results of the estimations using the ANN, LSSVM and PLS models were compared with the operation data, and the root-mean square error (RMSE) for each model was calculated to evaluate estimation performance. The RMSE of the LSSVM model 15.91, which turned out to be the best estimation. RMSE values for the ANN and PLS models were 17.24 and 21.31, respectively, indicating their relative estimation performance. The essential input parameters used in the models can be selected by sensitivity analysis. The RMSE for each model was calculated again after a sequential input selection process was used to remove insignificant input parameters. The RMSE of the LSSVM was then 13.21, which is better than the previous RMSE with all 16 parameters. The results show that LSSVM model using 13 input parameters can be utilized to calculate the required values for oxygen volume and coolant needed to optimally adjust the steel target temperature.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권4호
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• pp.247-253
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• 2011

A sustainability of electricity supply has emerged as a critical issue for low carbon green growth in South Korea. Wind power is the fastest growing source of renewable energy. However, due to its own intermittency and volatility, the power supply generated from wind energy has variability in nature. Hence, accurate forecasting of wind speed and power plays a key role in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. This paper presents a short-term wind speed prediction method based on support vector regression. Moreover, particle swarm optimization is adopted to find an optimum setting of hyper-parameters in support vector regression. An illustration is given by real-world data and the effect of model regularization by particle swarm optimization is discussed as well.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2001년도 춘계학술대회 논문집
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• pp.44-48
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• 2001

Tube hydroforming technology has increased dramatically, mainly by automotive industry in europe and the americas. It is required tube formability, optimized with regard to tribological factors and specially designed die and presses. In this process has many important parameters as expansion ratio of a tube, axial feeding, internal pressure and preforming low pressure. The following paper discusses to combine forming factors and expectation of manufacture problem by hydroforming of automotive radiator support member.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1187-1192
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• 2008

In this paper, a versatile multi-objective optimization concept for fatigue life prediction is introduced. Multi-objective decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• 한국경영과학회지
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• 제30권1호
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• pp.55-74
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• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• 소성∙가공
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• 제9권6호
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• pp.638-643
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• 2000

This study Is concerned with the development of design support program for deep drawing process. The present support program is designed to generate the layout drawings by utilizing the following key functions: analysis of product shape, generation of key stages by pattern database, determination of layout generation method, generation of layout. furthermore, from the results by process design program input data for simulation Is automatically generated with appropriate process parameters and connected seamlessly to carry out the finite element analysis so that the design can be checked for the possible problems in real manufacturing process. The designer can generate layout drawings and test the design by simulation quickly and conveniently In these system designer can verify and optimize the design. We tested this system for various type of product shape md found that the generated layout is in good agreement with the real cases.

• Journal of the Korean Data and Information Science Society
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• 제21권6호
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• pp.1319-1325
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• 2010

Quantile regression provides a more complete statistical analysis of the stochastic relationships among random variables. Sometimes quantile functions estimated at different orders can cross each other. We propose a new non-crossing quantile regression method applying support vector median regression to restricted regression quantile, restricted support vector quantile regression. The proposed method provides a satisfying solution to estimating non-crossing quantile functions when multiple quantiles for high dimensional data are needed. We also present the model selection method that employs cross validation techniques for choosing the parameters which aect the performance of the proposed method. One real example and a simulated example are provided to show the usefulness of the proposed method.

• Journal of the Korean Data and Information Science Society
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• 제23권2호
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• pp.393-401
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• 2012

This paper deals with the estimations of the least squares support vector regression when the responses are subject to randomly right censoring. The estimation is performed via two steps - the ordinary least squares support vector regression and the least squares support vector regression with censored data. We use the empirical fact that the estimated regression functions subject to randomly right censoring are close to the true regression functions than the observed failure times subject to randomly right censoring. The hyper-parameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation function. Experimental results are then presented which indicate the performance of the proposed procedure.