• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.685-696
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• 1999

We present local and semilocal convergence results for New-ton's method in a Banach space setting. In particular using Lipschitz-type assumptions on the second Frechet-derivative we find results con-cerning the radius of convergence of Newton's method. Such results are useful in the context of predictor-corrector continuation procedures. Finally we provide numerical examples to show that our results can ap-ply where earlier ones using Lipschitz assumption on the first Frechet-derivative fail.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.203-206
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• 1996

Prediction of firm bankruptcy have been extensively studied in accounting, as all stockholders in a firm have a vested interest in monitoring its financial performance. The objective of this paper is to develop the hybrid models for bankruptcy prediction. The proposed hybrid models are two phase. Phase one are (a) DA-assisted neural network, (b) Logit-assisted neural network, and (c) Genetic-assisted neural network. And, phase two are (a) DA-assisted Case based reasoning, and (b) Genetic-assisted Case based reasoning. In the variables selection, We are focusing on three alternative methods - linear discriminant analysis, logit analysis and genetic algorithms - that can be used empirically select predictors for hybrid model in bankruptcy prediction. Empirical results using Korean medium-sized firms data show that hybrid models are very promising neural network models and case based reasoning for bankruptcy prediction in terms of predictive accuracy and adaptability.

• Journal of Welding and Joining
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• v.32 no.2
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• pp.43-47
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• 2014

Famous artificial neural network (ANN) is applied to predict proper process window of arc welding. Target weldment is variously combined lap joint fillet welding of automotive steel plates. ANN's system variable such as number of hidden layers, perceptrons and transfer function are carefully selected through case by case test. Input variables are welding condition and steel plate combination, for example, welding machine type, shield gas composition, current, speed and strength, thickness of base material. The number of each input variable referred in welding experiment is counted and provided to make it possible to presume the qualitative precision and limit of prediction. One of experimental process windows is excluded for predictability estimation and the rest are applied for neural network training. As expected from basic ANN theory, experimental condition composed of frequently referred input variables showed relatively more precise prediction while rarely referred set showed poorer result. As conclusion, application of ANN to arc welding process window derivation showed comparatively practical feasibility while it still needs more training for higher precision.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1997.10a
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• pp.111-124
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• 1997

With the combination of existing tidal predictio model and numerical tidal model, the efficient tidal prediction system was formulated and applied to the neighboring area of Pusan port. Because all tidal constituents for prediction (normally 69 constituents are used) can't be considered due to difficulties on computing efforts, some errors between the observed and predicted values were inevitably occurred. But it was confirmed that the practical results with about 10% of relative errors were obtained if four major tidal constituents(M$_2$, S$_2$. $K_1$, $O_1$) are used at least. Thus, if other constituents than four major tidal constituents are additornaly used, more accurate results will be obtained . Furthermore, if the databases of harmonic constants in coastal waters is made in advance using the numberical tidal model, prompt tidal prediction could be achieved whenever required.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.137-137
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• 2010

Copper electroplating is a very popular and important technology for depositing high-quality conductor interconnections, especially in through silicon via (TSV). As this advanced packaging technique developing, a mass of copper and chemical solution are used, so attention to these chemical materials into the utilization and costs can not be ignored. An economical and practical real-time chemical solution monitoring has not been achieved yet. Either Red-green-blue (RGB) or optical emission spectroscopy (OES) color sensor can successfully monitor the color condition of solution during the process. The reaction rate, uniformity and quality can map onto the color changing. Hidden Semi Markov model (HSMM) can establish mapping from the color change to upper indicators, and artificial neural network (ANN) can be integrated to comprehensively determine its targets, whether the solution inside the container can continue to use.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.7
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• pp.1042-1049
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• 1997

LMFBR(Liquid Metal Fast Breeder Reactor) vessel is operated under the high temperatures of 500-550.deg. C. Thus, transient thermal loads were severe enough to cause inelastic deformation due to creep-fatigue and plasticity. For reduction of such inelastic deformations, Y-piece structure in the form of a thermal sleeve is used in LMFBR vessel under repeated start-up, service and shut-down conditions. Therefore, a systematic method for inelastic analysis is needed for design of the Y-piece structure subjected to such loading conditions. In the present investigation, finite element analysis of heat transfer and inelastic thermal stress were carried out for the Y-piece structure in LMFBR vessel under service conditions. For such analysis, ABAQUS program was employed based on the elasto-plastic and Chaboche viscoplastic constitutive equations. Based on numerical data obtained from the analysis, creep-fatigue damage estimation according to ASME Code Case N-47 was made and compared to each other. Finally, it was found out that the numerical predictio of damage level due to creep based on Chaboche unified viscoplastic constitutive equation was relatively better compared to elasto-plastic constitutive formulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.468-474
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• 2017

A test service for the weapon systems evaluation is one of the most important processes during the weapon systems acquisition or development life cycle. Before completion of weapon systems development, the appropriate evaluation test can reduce risk and expense which might be expected during weapon systems development procedure. In this paper, it is suggested that a probabilistic prediction method based on Monte Carlo simulation for how much the annual weapon systems evaluation test excution ratio can be reached compared to the yearly initial planned test quantity. And then a weapon systems evaluation test quantitative management scheme is suggested to assist decision making for the test schedule manager who can arrange monthly test schedule based on the prediction result of annual test excution ratio. And the proposed method is applied for the weapon systems evaluation firing test data of the 8th directorate, Agency for Defense Development(ADD). And also the application result is examined.