• 한국정보시스템학회지:정보시스템연구
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• 제5권
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• pp.205-248
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• 1996

Historically, the en-users' acceptance of the expert systems(ES) have generally been used as a proxy for the ES' implementation success by both practitioners and academicians. However, with regard to bank loan decisions, most loan officers approach the acquisition of an ES with apprehension. In order to overcome this skepticism, more research should focus on the behavioral aspects relate to systems acquisition and usage. This research applied Vroom's(1964) expectancy theory in an effort to predict end-users' motivation to use an ES in a bank loan decision context. Because human behaviors and judgements are nonlinear rather than linear functions, accurately predicting human behavior is very difficult. To increase the prediction power for end-users' motivation to use an ES in a bank loan decision context, this research used an artificial neural network (ANN) model. In this research, an attempt was made to evaluate adequacy of the surrogates by analyzing differences between real bank loan officers and student surrogates in applying expectancy theory to estimate bank loan officers' motivation to use ES in a bank loan decision context.

• 콘크리트학회논문집
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• 제12권2호
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• pp.31-42
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• 2000

This paper discusses the validity of models predicting the compressive strength of concrete subjected to various temperature histories and the shortcomings of existing rate constant model and apparent activation energy concept. Based on the discussion, a modified rate constant model is proposed. The modified rate constant model, in which apparent activation energy is a nonlinear function of curing temperature and age, accurately estimates the development of the experimental compressive strengths by a few researchers. Also, the apparent activation energy of concrete cured with high temperature decreases rapidly with age, but that of concrete cured with low temperature decreases gradually with age. Finally generalized models to predict apparent activation energy and compressive strength are proposed, which are based on the regression results.

• Journal of the Korean Data and Information Science Society
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• 제20권2호
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• pp.445-452
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• 2009

Credibility models are actuarial tools to distribute premiums fairly among a heterogeneous group of policyholders. Many existing credibility models can be expressed as special cases of linear mixed effects models. In this paper we propose a nonlinear credibility regression model by reforming the linear mixed effects model through kernel machine. The proposed model can be seen as prediction method applicable in any setting where repeated measures are made for subjects with different risk levels. Experimental results are then presented which indicate the performance of the proposed estimating procedure.

• 한국전산유체공학회지
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• 제13권3호
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• pp.1-7
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• 2008

A supersonic base flow is computed to investigate the effect of the eddy viscosity coefficient to the linear ${\kappa}-{\varepsilon}$ turbulence models. Slight modifications to the eddy viscosity coefficient, which are based on the realizability condition, are given to the Launder-Sharma turbulence model so that present models satisfy the realizability condition. Numerical results for supersonic base flow show that turbulence models with the weaky-nonlinear eddy viscosity coefficient can lead to reasonable enhancements in the prediction of the velocity and turbulent kinetic energy profiles.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1315-1321
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• 2005

Using hyper-elastic material has been increased gradually and its range was extended all over the industrial. In addition, the performance prediction of this material was required not only experimental methods like metal material but also numerical methods. In this study, we presented the process how to use numerical method for hyper-elastic material and then, it was applied for seat-ring of butterfly valve by using this process. The finite element analysis was executed to evaluate the mechanical characteristics of hyper-elastic material and search the optimum model considered conditions and features. According to that model the coefficient was obtained by using Contact analysis.

• 응용통계연구
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• 제20권2호
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• pp.219-227
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• 2007

시계열 모형은 통신망 트래픽의 예측과 분석에 유용하게 쓰여 왔다. 본 논문에서는 통신망 트래픽의 예측을 위하여 다양한 시계열 모형을 소개하고 성능평가를 하고자 한다. 이를 위하여 실제 통신망 트래픽 자료에 선형 및 비선형 시계열모형을 적합 시키고 비선형 시계열모형이 선형 시계열 모형보다 예측의 정확도가 우수함을 보이고자 한다.

• 한국농공학회지
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• 제39권2호
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• pp.19-25
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• 1997

Abstract [] The prediction of changes in the tidal regime due to the sea dike closure in the Saemankum area was performed using the nonlinear finite element model, TIDE. Based upon an overall comparison of calibrated model results with available field data, the TIDE model behaves well and is good representation of the hydrodynamic of the Saemankum tidal project area. It is shown that the TIDE model does an excellent job of computing the changes of tidal characteristics resulting in sea dike closure in an estuary area.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2002년도 봄 학술발표회 논문집
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• pp.545-550
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• 2002

Concrete is one of the essential structural materials in the construction. But, concrete consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructor. Therefore, concrete mixes depend on experiences of experts. However, it is more and more difficult to determine concrete mixes design by empirical means because more ingredients like mineral and chemical admixtures are included. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network are used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength and slump are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2004년도 춘계 학술발표회 제16권1호
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• pp.738-741
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• 2004

This study is concerning on modeling to predict the flexural behaviors of FRP-confined concrete structural members. For compressive behaviors of confined concrete by FRP jackets, the hypoelasticity-based constitutive law of concrete has been presented under the basis of three-dimensional stress states. The strength enhancement of concrete wrapped by FRP jackets has been determined by the failure surface of concrete in tri-axial states, and its corresponding peak strain is computed by the strain enhancement factor. The behavior of FRP jackets has been modeled using the mechanics of orthotropic laminated composite materials in two-dimensional stress states. To be based on the three-dimensional constitutive laws, an algorithm for the prediction of flexural bending behaviors of FRP-confined concrete structural member has been presented.

• 품질경영학회지
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• 제31권2호
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• pp.165-182
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• 2003

The fatigue has been considered to the most important failure mode where optimal design or reliability prediction of the machinery in aircraft, atomic reactors, and structure systems, etc., is required. When the statistical analysis of fatigue life data is performed, some difficulties are present because of the following facts : nonlinear relationship, heteroscedastic data, large scatter in the data, censored data (runouts), and existence of fatigue limit. To find the S-N curve models that characterize fatigue strength better, this research compares existing fatigue curve models developed recently in terms of the residual mean square and the estimate of fatigue limit, etc. for various fatigue data sets.