• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.191-194
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• 2006

대학에서 학생 개인의 학업성취도를 나타내는 평점평균(GPA)은 많은 요인의 영향을 받는 것으로 알려져 있다. 본 연구에서는 현행입시제도하에서 획득 가능한 자료를 이용하여 학생부 성적과 수학능력시험성적이 대학의 학업성취도를 나타내는 평점평균과 어떠한 관계를 갖고 있는지 일반화선형모형(GLM)을 이용하여 통계적으로 분석 평가하고자 한다. 여기서 얻어진 결과는 2008학년도부터 적용되는 제7차 교육과정의 수학능력시험성적과 학생부 성적 반영 비율 산정에 필요한 기초적 정보를 제공하는데 도움이 될 수 있으리라 믿어진다. 분석에 사용한 자료는 2003, 2004학년도 인제대학교에 입학한 학생들의 입학성적과 2003, 04, 05학년도의 평점평균을 대상으로 삼았다.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.765-777
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• 2009

Our study aimed to illustrate long term trend in 10 micrometer particular matters excluding confounding effect. Daily 10 micrometer particular matters data were measured in 27 places and meteorological data (maximum temperature, humidity and maximum wind speed, solar radiation) were obtained from the national institute of environmental research for the period from January, 1996 to December 2000. To estimate the increasing and decreasing long term trend in a set of observed data, set up the model. The model included regression spline smooth function on the time and meteorological factors to capture the seasonal time trend and any possible nonlinear relationship. The result was estimated to decrease slightly after adjusting for meteorological factors and seasonal time trend.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.727-739
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• 2002

Based on a generalized variational principle for magneto-thermo-elasticity, a theoretical model is proposed to describe the coupled magneto-thermo-elastic interaction in soft ferromagnetic plates. Using the linearized theory of magneto-elasticity and perturbation technique, we analyze the magneto-elastic and magneto-thermo-elastic instability of simply supported ferromagnetic plates subjected to thermal and magnetic fields. A nonlinear finite element procedure is developed next to simulate the magneto-thermo-elastic behavior of a finite-size ferromagnetic plates. The effects of thermal and magnetic fields on the magneto-thermo-elastic bending and buckling is investigated in some detail.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.148-148
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• 2011

Riemann 문제는 천수방정식과 같은 쌍곡선형 방정식과 단일한 도약에 의해 불연속인 어떤 점의 좌 우에서 상수인 자료로 구성되는 초기치 문제로서 그 해법은 Godunov 방법과 같이 정확해에 의하면 정확 Riemann 해법, 근사 기법에 의하면 근사 Riemann 해법으로 불린다. 지금까지 이용되는 근사 Riemann 해법으로는 1981년에 P. L. Roe가 제안한 Roe의 선형화 기법과 1983년에 A. Harten, P. D. Lax, 그리고 B. van Leer가 제안한 HLL 기법의 수정 기법들이다. 최대 및 최소 파속만 고려하는 것으로 알려진 HLL 기법은 1988년에 B. Einfeldt의 제안에 의해 두 파속의 결정에서 Roe의 선형화 기법에 따른 고유치와 비교하는 것으로 수정되었다(HLLE 기법). 또한, 1994년에 E. F. Toro 등은 접촉파를 고려하기 위해 선형화된 지배방정식의 정확해로부터 중앙 파속을 고려하는 기법을 제안하였고, 이를 HLLC 기법으로 불렀다. 2002년에 T. Linde는 중앙 파속을 평가하기 위해 일반화된(수학적) 엔트로피 함수를 도입하였으며, van Leer는 이를 HLLL 기법으로 불렀다. 이 기법에서는 접촉파의 평가를 위해 보존변수에 대한 일반화된 엔트로피 함수로부터 중앙 파속이 유도되며, 이것과 특성 속도의 비교를 통해 최대 및 최소 파속이 결정된다. 따라서 이 기법에서는 모든 파속이 초기치로부터 결정되므로 HLLE 기법과 달리 Roe의 선형화 기법과 완전히 결별되고 HLLC 기법과 달리 정확해에 의존되지 않는 점에서 HLLL 기법은 모태인 HLL 기법의 온전한 계승으로 볼 수 있다. HLLL 기법은 여러 분야에 적용된 바 있으나, 수공학 분야에 적용된 사례는 알려진 바 없다. 이는 천수방정식에 대한 (물리적) 엔트로피 함수가 명확하지 않기 때문인 것으로 보인다. 이 연구에서는 보존변수로부터 정의되는 총 에너지를 일반화된 엔트로피 함수로 간주하여 모형을 구성하고, 정확해가 알려진 1차원 문제에 대해 적용성을 검토하였다. 정확해가 알려진 경우에 대해 모의한 결과, 1차 정도 수치해의 한계에도 불구하고, HLLL 기법의 결과는 대체로 정확해와 잘 일치하였으며 그 외의 HLL-형 기법의 그것에 비해 우수한 것으로 나타났다. 특히, 물이 빠져 바닥이 드러나는 상태에 대한 접촉 파속의 추정에서 Riemann 불변량을 이용하는 HLLC 기법에 비해 물이 빠지는 전선을 더 정확하게 포착하는 HLLL 기법의 결과는 매우 고무적이었다.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.343-348
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• 2005

The goal of this paper is to study the joint effect of factors of neural network teaming procedure. There are many factors, which may affect the generalization ability and teaming speed of neural networks, such as the initial values of weights, the learning rates, and the regularization coefficients. We will apply a constructive training algerian for neural network, then patterns are trained incrementally by considering them one by one. First, we will investigate the effect of these factors on generalization performance and learning speed. Based on these factors' effect, we will propose a joint method that simultaneously considers these three factors, and dynamically hue the learning rate and regularization coefficient. Then we will present the results of some experimental comparison among these kinds of methods in several simulated nonlinear data. Finally, we will draw conclusions and make plan for future work.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.157-168
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• 2009

The random utility theory and the multinomial logit model (including a more recent variant--the mixed multinomial logit) derived from it have constituted a back bone for theoretical and empirical analyses of various travel demand features including mode choice. In their empirical applications, however, it is customary to specify random utilities which are linear in modal attributes such as time and cost, and in socio-economic variables. The linearity helps easy derivation of important information such as value of travel time savings by calculating marginal rate of substitution between time and cost. In this paper the author focuses on the very linearity of the random utilities. Taking into account the fact that the mode chooser is also labour supplier, commodity consumer as well as leisure-seeker, the author sets up a maximization model of the traveller, which encompasses various economic activities of the traveller. The author derive from the model the indifference curve defined on the space of modal attributes, time and cost and investigate under what conditions the random utility of the traveller becomes linear. It turns out that there exist the conditions under which the random utility is really linear in modal attributes, but the property does not hold when the traveller has a corner solution on the space of modal attributes, or when the primary utility function of the traveller is directly affected by labour provided and/or the travel time itself. As a corollary of the analysis, a random utility is suggested, approximated up to the second order of the variables involved for empirical studies of the field.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1173-1181
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• 2012

In order to suggest the basic resources of mathematics education to the specialized high school, we investigate the attitude of students about mathematics education. Questionnaires survey was carried on 654 students and we use the statistical analysis such as chi-square test, gamma, generalized linear model, Anova, regression. Several result can be derived from the questionnaire analysis. There are differences between the general and specialized high school students in the interest, pre-learning ability etc. The specialized school students think the usefulness of mathematics more importantly, while the general school students think more closely related to their course.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.455-467
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• 2003

There has been a long debate on the applicability of the chi-square approximation to statistics based on small sample size. Extending comparison results among Pearson chi-square Χ$^2$, generalized likelihood .ratio G$^2$, and the power divergence Ι(2/3) statistics suggested by Rudas(1986), recently developed disparity statistics (BWHD(1/9), BWCS(1/3), NED(4/3)) we compared and analyzed in this paper. By Monte Carlo studies about the independence model of two dimension contingency tables, the conditional model and one variable independence model of three dimensional tables, simulated 90 and 95 percentage points and approximate 95% confidence intervals for the true percentage points are obtained. It is found that the Χ$^2$, Ι(2/3), BWHD(1/9) test statistics have very similar behavior and there seem to be applcable for small sample sizes than others.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.71-80
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• 2001

Logistic regression model is one of the most popular linear models for a binary response variable and used for the estimation of probability function. In many practical situations, the probability function can be expressed by a bell shaped curve and such a function can be estimated by a second order logistic regression model. However, when the probability curve is asymmetric, the estimation results using a second order logistic regression model may not be precise because a second order logistic regression model is a symmetric function. In addition, even if a second order logistic regression model is used, the interpretation for the effect of second order term may not be easy. In this paper, in order to alleviate such problems, an estimation method for asymmetric probabiity curve based on a first order logistic regression model and iterative bi-section method is proposed and its performance is compared with that of a second order logistic regression model by a simulation study.