• Journal of Information Processing Systems
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• v.20 no.2
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• pp.263-272
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• 2024

A model based on genetic algorithm optimization, GA-SVM, is proposed to warn university students of their status. This model improves the predictive effect of support vector machines. The genetic optimization algorithm is used to train the hyperparameters and adjust the kernel parameters, kernel penalty factor C, and gamma to optimize the support vector machine model, which can rapidly achieve convergence to obtain the optimal solution. The experimental model was trained on open-source datasets and validated through comparisons with random forest, backpropagation neural network, and GA-SVM models. The test results show that the genetic algorithm-optimized radial basis kernel support vector machine model GA-SVM can obtain higher accuracy rates when used for early warning in university learning.

• Korean Chemical Engineering Research
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• v.52 no.3
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• pp.307-313
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• 2014

In this study, an optimization process design has been performed to separate 99.9 mol% of Isobutyl Acetate from binary azeotropic mixture of Isobutyl Acetate and Isobutyl Alcohol system using a Pressure Swing Distillation (PSD). PSD is used to separate binary azeotropic mixtures using the difference between the relative volatilities and azeotropic compositions by changing the system pressure. Non-Random Two Liquid (NRTL) model for liquid phase and the Peng-Robinson equation for vapor phase are used. An optimization study for the reflux ratio and feed stage locations which minimize the total reboiler heat duties are studied. Since PSD process consists of two columns, i.e. high pressure and low pressure, the effect of column sequence on the optimum conditions is reported.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.77-82
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• 2019

The purpose of this study is to analyze the relationship between the controlling shareholding ratio and the business diversification of savings banks The difference in this study is the analysis of the relationship between the controlling shareholding ratio of the savings bank and the business diversification using panel data. In this study, the semi-annual financial statements for the period 2014-2018 were used on the basis of a sample of 79 saving banks. The research model is analyzed using random effects generalized linear square (GLS) model considering the autocorrelation problem. As a result of the empirical analysis, it is estimated that the relationship between the controlling shareholding ratio of the savings bank and the business diversification is significant (+). This is the result of supporting the hedging hypothesis.

• Korean Journal of Legislative Studies
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• v.23 no.2
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• pp.147-177
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• 2017

Although a number of empirical studies found that political ideology plays a significant role in Korean elections, they entirely rely on cross-sectional data analysis. In contrast to previous research, this study investigates the effects of ideology in the 2012 Korean presidential election through standard panel data analysis. Specifically, using "EAI Panel Study, 2012", the effects of ideology on both candidate evaluation and vote choice were examined via fixed effects, random effects, and pooled regression analysis. And the results from applying the two most popular models of ideological voting, the proximity model and the directional change model were also compared. The results show that candidate evaluations and vote choice during the election (April, 2012- December, 2012) were significantly influenced by the ideological difference between voters and candidates, independent from partisanship and other standard socio-demographic factors. And this ideological voting during the election seems better captured by the directional change model than by the proximity model.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.310-315
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• 2003

This paper presents the effect of boundary condition of failure pressure model for buried pipelines on failure prediction by using a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with various corrosion defects for long exposure periods in years. A failure pressure model based on a failure function composed of failure pressure and operation pressure is adopted for the assessment of pipeline failure. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically studied by using a failure probability model for the corrosion pipeline.

• Korean System Dynamics Review
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• v.12 no.4
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• pp.157-175
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• 2011

The purpose of this paper is to find out the effects of the gambler's fallacy bias on the supply chain. For this study, the simulation was based on a casual structure of the Beer Distribution Game from Sterman(2000)'s Business Dynamics and designed into 2 different models : the first model carries the exact same structure as the reference mentioned above and for the second model, the comparison model is used reflecting gambler's fallacy bias. Each model has 2 different demand patterns. The 4 cases of models was tested with 1,000 different random number seeds. The results for the simulation are following : In the aspect of the inventory and out of stock, the basic model resulted better than the comparison. However, in the bullwhip effect, the comparison model has less than the basic in terms of the level demand pattern. But there was no significant difference in the cycle demand.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.353-360
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• 2015

Various statistical models have been proposed over the last decade for spatially correlated Gaussian outcomes. The spatial linear mixed model (SLMM), which incorporates a spatial effect as a random component to the linear model, is the one of the most widely used approaches in various application contexts. Employing link functions, SLMM can be naturally extended to spatial generalized linear mixed model for non-Gaussian outcomes (SGLMM). We review popular SGLMMs on non-Gaussian spatial outcomes and demonstrate their applications with available public data.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.121-131
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• 2020

This study aims to investigate the interplay between education and local roads on Foreign Direct Investment (FDI) in the Philippines, using economic growth as an instrument. The study used the quantitative research design applying both descriptive and inferential statistics. A combination of Two Stage Least Square Regression Model and three approaches in Panel Regression Model such as Pooled Least Square, Fixed Effect Model, and Random Effect Model were utilized in order to study the effects of education and local roads on foreign direct investment of the Philippines. Based on Fixed Effect regression results, higher education graduates and local road investments, as conditioned by economic growth, were significant factors in order to increase the foreign direct investment in the Philippines. Accordingly, a unit increase in higher education graduates, as conditioned by economic growth, leads to 8.758 unit increases in the foreign direct investment. While, a unit increased in local road investments, as conditioned by economic growth, leads to a 0.002 decrease in foreign direct investment. The regression results of the study suggest that the Foreign Direct Investment in the regions such as CAR, I, II, IV-B, V, VIII, IX, X, XI, XII, XIII, and ARMM are higher compared to Region IV-A.

• Korean Journal of Agricultural Science
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• v.41 no.4
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• pp.481-485
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• 2014

According to statistical data the past ten years, cultivation area and yield of radish are steadily decreasing. This phenomenon cause instability of radish's supply due to meteorological chage, even if radish's yield per unit area is increasing by cultivation technological development. These problems raise radish's price. So, we conducted study on meteorological factors for accuracy improvement of radish yield estimation. Panel analysis was used with two-way effect model considering group effect and time effect. As the result, we show that mixed effects model (fixed effect: group, random effects: time) was statistical significance. According to the model, a rise of one degree in the average air temperature on August will decrease radish's yield per unit area by $428kg{\cdot}10a^{-1}$ and that in the average air temperature on October will increase radish's yield per unit area by $438kg{\cdot}10a^{-1}$. The reason is that radish's growth will be easily influenced by meteorological condition of a high temperature on August and by meteorological condition of a low temperature on Octoboer.

• Journal of Family Resource Management and Policy Review
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• v.19 no.3
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• pp.1-16
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• 2015

The purpose of this study was to synthesize the results of studies on the effects of multi-cultural education program for Korean children. Using the author's own selection criteria, 17 studies were finally selected and 31 effect sizes were calculated from these studies and used for meta analysis. The overall effect size for all studies on the random effect model was .802, and it was positive and high. Given the heterogeneity among the effect size, subgroup analysis was conducted. According to the analysis, effect sizes significantly differed depending on program goal, concerned multi-cultural higher than others. Result also showed that the high scored effect sizes were the general family, pre-school age children group, and the program were 11-20 children group in size, and 11~20 times in frequency of education.